diff --git a/output_ft_more_layers_books3_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-books3-8e-05/checkpoint-540/adapter_model.safetensors b/output_ft_more_layers_books3_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-books3-8e-05/checkpoint-540/adapter_model.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..222a4a95539c12a3eefb8ae8d0c87eeebc03a900
--- /dev/null
+++ b/output_ft_more_layers_books3_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-books3-8e-05/checkpoint-540/adapter_model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d29222ac3f3fa513bacd1245deaa16d781e9f0c1dcee2e3f7a853b262252fb5f
+size 67144544
diff --git a/output_ft_more_layers_github_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-github-8e-05/checkpoint-290/adapter_model.safetensors b/output_ft_more_layers_github_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-github-8e-05/checkpoint-290/adapter_model.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..e0598fadfb693414e2946c3ff66e44627ce0116b
--- /dev/null
+++ b/output_ft_more_layers_github_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-github-8e-05/checkpoint-290/adapter_model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5a73cce5dd1be3d6c0200bc9d747cc7ce6d3d45a917ebe81cfaec65a64fc6cdc
+size 67144544
diff --git a/output_ft_more_layers_gutenberg_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-gutenberg-8e-05/checkpoint-675/adapter_model.safetensors b/output_ft_more_layers_gutenberg_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-gutenberg-8e-05/checkpoint-675/adapter_model.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..9ef08493efdcf08baaf80a4c99ead2b0838b8d1d
--- /dev/null
+++ b/output_ft_more_layers_gutenberg_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-gutenberg-8e-05/checkpoint-675/adapter_model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:445316158457ca094eed5471f00e77cce05ea294e2de51e42c30772ccac295b0
+size 67144544
diff --git a/output_ft_more_layers_gutenberg_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-gutenberg-8e-05/checkpoint-660/adapter_model.safetensors b/output_ft_more_layers_gutenberg_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-gutenberg-8e-05/checkpoint-660/adapter_model.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..8af7ff469aa9abf4c063ab170f06fbae71367235
--- /dev/null
+++ b/output_ft_more_layers_gutenberg_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-gutenberg-8e-05/checkpoint-660/adapter_model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dacab1dc80e2ce118ab37a4ae3e8962eec64e67d70f7a09dc49b7b7ac5fade2c
+size 67144544
diff --git a/output_ft_more_layers_hackernews_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-hackernews-8e-05/checkpoint-320/adapter_model.safetensors b/output_ft_more_layers_hackernews_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-hackernews-8e-05/checkpoint-320/adapter_model.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..fbab7e04430e9d508bf9618041d7edb8b21d0089
--- /dev/null
+++ b/output_ft_more_layers_hackernews_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-hackernews-8e-05/checkpoint-320/adapter_model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:001a5171cbc5098faa66b014357360fcedebb3b99dd82087cc8cec2e670550bc
+size 67144544
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-250/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-250/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..207dc64f3f3a5efa2452297b1a9c87ef0be2635b
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-250/trainer_state.json
@@ -0,0 +1,408 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 3.3333333333333335,
+  "eval_steps": 10,
+  "global_step": 250,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 4.096517996544e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-260/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-260/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-260/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-260/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-260/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-260/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-260/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-260/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..ead3bf8da824b71f22675334955bcdc64ec1ad57
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-260/trainer_state.json
@@ -0,0 +1,423 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 3.466666666666667,
+  "eval_steps": 10,
+  "global_step": 260,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 4.26037871640576e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-270/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-270/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-270/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-270/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-270/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-270/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-270/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-270/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..dfde10230570172e8595f7d04a791be51f5ee69e
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-270/trainer_state.json
@@ -0,0 +1,438 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 3.6,
+  "eval_steps": 10,
+  "global_step": 270,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 4.42423943626752e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-280/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-280/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-280/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-280/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-280/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-280/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-280/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-280/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..060771e398ae34021d508883d5fb26261b61176f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-280/trainer_state.json
@@ -0,0 +1,453 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 3.7333333333333334,
+  "eval_steps": 10,
+  "global_step": 280,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 4.58810015612928e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-290/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-290/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-290/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-290/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-290/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-290/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-290/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-290/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..550cba52ad37e69179c29fdd22a39297741e2706
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-290/trainer_state.json
@@ -0,0 +1,468 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 3.8666666666666667,
+  "eval_steps": 10,
+  "global_step": 290,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 4.75196087599104e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-300/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-300/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-300/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-300/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-300/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-300/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-300/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-300/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..1b26a915dc815fece759b8df365187746df162f0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-300/trainer_state.json
@@ -0,0 +1,483 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 4.0,
+  "eval_steps": 10,
+  "global_step": 300,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 4.9158215958528e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-310/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-310/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-310/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-310/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-310/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-310/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-310/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-310/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..ec70d18a9be1615e1e952354c4190f2fa679e86d
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-310/trainer_state.json
@@ -0,0 +1,498 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 4.133333333333334,
+  "eval_steps": 10,
+  "global_step": 310,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 5.07968231571456e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-320/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-320/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-320/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-320/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-320/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-320/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-320/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-320/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..3d4053f7040aab8c696adaff39aa19f5d1decbf3
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-320/trainer_state.json
@@ -0,0 +1,513 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 4.266666666666667,
+  "eval_steps": 10,
+  "global_step": 320,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 5.24354303557632e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-330/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-330/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-330/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-330/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-330/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-330/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-330/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-330/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..38c269271a117f436d3f50d3a004b38cde2c9f60
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-330/trainer_state.json
@@ -0,0 +1,528 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 4.4,
+  "eval_steps": 10,
+  "global_step": 330,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 5.40740375543808e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-340/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-340/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-340/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-340/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-340/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-340/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-340/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-340/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..4fb47d2db8c7f792b19a2b18c8dade914ccb52cc
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-340/trainer_state.json
@@ -0,0 +1,543 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 4.533333333333333,
+  "eval_steps": 10,
+  "global_step": 340,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 5.57126447529984e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-350/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-350/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-350/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-350/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-350/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-350/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-350/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-350/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..1dce32621617968c2237848ba3780da621d91d3a
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-350/trainer_state.json
@@ -0,0 +1,558 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 4.666666666666667,
+  "eval_steps": 10,
+  "global_step": 350,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 0.9267418384552002,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.0599,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.324584722518921,
+      "eval_runtime": 43.853,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 350
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 5.7351251951616e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-360/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-360/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-360/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-360/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-360/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-360/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-360/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-360/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..2db91a8405ecba28b8bc676d2e92fea2a315238c
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-360/trainer_state.json
@@ -0,0 +1,573 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 4.8,
+  "eval_steps": 10,
+  "global_step": 360,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 0.9267418384552002,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.0599,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.324584722518921,
+      "eval_runtime": 43.853,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 1.116028070449829,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.0048,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 1.3211394548416138,
+      "eval_runtime": 44.1843,
+      "eval_samples_per_second": 22.632,
+      "eval_steps_per_second": 2.829,
+      "step": 360
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 5.89898591502336e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-370/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-370/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-370/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-370/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-370/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-370/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-370/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-370/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..31b5675fd0c190b1ac91cb4588ab96ff52407127
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-370/trainer_state.json
@@ -0,0 +1,588 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 4.933333333333334,
+  "eval_steps": 10,
+  "global_step": 370,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 0.9267418384552002,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.0599,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.324584722518921,
+      "eval_runtime": 43.853,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 1.116028070449829,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.0048,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 1.3211394548416138,
+      "eval_runtime": 44.1843,
+      "eval_samples_per_second": 22.632,
+      "eval_steps_per_second": 2.829,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 1.0464606285095215,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.0147,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 1.3230206966400146,
+      "eval_runtime": 44.0559,
+      "eval_samples_per_second": 22.698,
+      "eval_steps_per_second": 2.837,
+      "step": 370
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 6.06284663488512e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-380/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-380/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-380/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-380/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-380/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-380/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-380/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-380/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..445df87455ef1b9c9bc136e701d4ba8796a24275
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-380/trainer_state.json
@@ -0,0 +1,603 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 5.066666666666666,
+  "eval_steps": 10,
+  "global_step": 380,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 0.9267418384552002,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.0599,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.324584722518921,
+      "eval_runtime": 43.853,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 1.116028070449829,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.0048,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 1.3211394548416138,
+      "eval_runtime": 44.1843,
+      "eval_samples_per_second": 22.632,
+      "eval_steps_per_second": 2.829,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 1.0464606285095215,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.0147,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 1.3230206966400146,
+      "eval_runtime": 44.0559,
+      "eval_samples_per_second": 22.698,
+      "eval_steps_per_second": 2.837,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 1.1091907024383545,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.0073,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 1.3765190839767456,
+      "eval_runtime": 44.0219,
+      "eval_samples_per_second": 22.716,
+      "eval_steps_per_second": 2.839,
+      "step": 380
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 6.22670735474688e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-390/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-390/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-390/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-390/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-390/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-390/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-390/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-390/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..4bc64883665552cc86828b97e080365e08f19d30
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-390/trainer_state.json
@@ -0,0 +1,618 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 5.2,
+  "eval_steps": 10,
+  "global_step": 390,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 0.9267418384552002,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.0599,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.324584722518921,
+      "eval_runtime": 43.853,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 1.116028070449829,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.0048,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 1.3211394548416138,
+      "eval_runtime": 44.1843,
+      "eval_samples_per_second": 22.632,
+      "eval_steps_per_second": 2.829,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 1.0464606285095215,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.0147,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 1.3230206966400146,
+      "eval_runtime": 44.0559,
+      "eval_samples_per_second": 22.698,
+      "eval_steps_per_second": 2.837,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 1.1091907024383545,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.0073,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 1.3765190839767456,
+      "eval_runtime": 44.0219,
+      "eval_samples_per_second": 22.716,
+      "eval_steps_per_second": 2.839,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 1.3128504753112793,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.0126,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 1.3743306398391724,
+      "eval_runtime": 43.9063,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 390
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 6.39056807460864e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-400/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-400/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-400/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-400/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-400/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-400/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-400/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-400/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..ebfa38e5da374475966c34cef769dea6aa2006ed
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-400/trainer_state.json
@@ -0,0 +1,633 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 5.333333333333333,
+  "eval_steps": 10,
+  "global_step": 400,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 0.9267418384552002,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.0599,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.324584722518921,
+      "eval_runtime": 43.853,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 1.116028070449829,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.0048,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 1.3211394548416138,
+      "eval_runtime": 44.1843,
+      "eval_samples_per_second": 22.632,
+      "eval_steps_per_second": 2.829,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 1.0464606285095215,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.0147,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 1.3230206966400146,
+      "eval_runtime": 44.0559,
+      "eval_samples_per_second": 22.698,
+      "eval_steps_per_second": 2.837,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 1.1091907024383545,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.0073,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 1.3765190839767456,
+      "eval_runtime": 44.0219,
+      "eval_samples_per_second": 22.716,
+      "eval_steps_per_second": 2.839,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 1.3128504753112793,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.0126,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 1.3743306398391724,
+      "eval_runtime": 43.9063,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 1.2510898113250732,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 0.9869,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 1.3918826580047607,
+      "eval_runtime": 43.9264,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 400
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 6.5544287944704e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-410/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-410/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-410/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-410/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-410/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-410/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-410/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-410/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..9e4a3e84bb844fda629b2abd00620f9b316895ba
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-410/trainer_state.json
@@ -0,0 +1,648 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 5.466666666666667,
+  "eval_steps": 10,
+  "global_step": 410,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 0.9267418384552002,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.0599,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.324584722518921,
+      "eval_runtime": 43.853,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 1.116028070449829,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.0048,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 1.3211394548416138,
+      "eval_runtime": 44.1843,
+      "eval_samples_per_second": 22.632,
+      "eval_steps_per_second": 2.829,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 1.0464606285095215,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.0147,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 1.3230206966400146,
+      "eval_runtime": 44.0559,
+      "eval_samples_per_second": 22.698,
+      "eval_steps_per_second": 2.837,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 1.1091907024383545,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.0073,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 1.3765190839767456,
+      "eval_runtime": 44.0219,
+      "eval_samples_per_second": 22.716,
+      "eval_steps_per_second": 2.839,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 1.3128504753112793,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.0126,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 1.3743306398391724,
+      "eval_runtime": 43.9063,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 1.2510898113250732,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 0.9869,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 1.3918826580047607,
+      "eval_runtime": 43.9264,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 1.3030422925949097,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 0.9687,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 1.39524245262146,
+      "eval_runtime": 43.9233,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 410
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 6.71828951433216e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-420/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-420/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-420/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-420/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-420/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-420/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-420/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-420/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..31006c038304382d32f31a8a8881e5e31234c174
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-420/trainer_state.json
@@ -0,0 +1,663 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 5.6,
+  "eval_steps": 10,
+  "global_step": 420,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 0.9267418384552002,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.0599,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.324584722518921,
+      "eval_runtime": 43.853,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 1.116028070449829,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.0048,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 1.3211394548416138,
+      "eval_runtime": 44.1843,
+      "eval_samples_per_second": 22.632,
+      "eval_steps_per_second": 2.829,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 1.0464606285095215,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.0147,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 1.3230206966400146,
+      "eval_runtime": 44.0559,
+      "eval_samples_per_second": 22.698,
+      "eval_steps_per_second": 2.837,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 1.1091907024383545,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.0073,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 1.3765190839767456,
+      "eval_runtime": 44.0219,
+      "eval_samples_per_second": 22.716,
+      "eval_steps_per_second": 2.839,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 1.3128504753112793,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.0126,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 1.3743306398391724,
+      "eval_runtime": 43.9063,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 1.2510898113250732,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 0.9869,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 1.3918826580047607,
+      "eval_runtime": 43.9264,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 1.3030422925949097,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 0.9687,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 1.39524245262146,
+      "eval_runtime": 43.9233,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 1.395313024520874,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 0.9716,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 1.384624719619751,
+      "eval_runtime": 43.9592,
+      "eval_samples_per_second": 22.748,
+      "eval_steps_per_second": 2.844,
+      "step": 420
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 6.88215023419392e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-430/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-430/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-430/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-430/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-430/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-430/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-430/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-430/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..c1907047f403832919fa1d67d758a536d1442c85
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-430/trainer_state.json
@@ -0,0 +1,678 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 5.733333333333333,
+  "eval_steps": 10,
+  "global_step": 430,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 0.9267418384552002,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.0599,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.324584722518921,
+      "eval_runtime": 43.853,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 1.116028070449829,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.0048,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 1.3211394548416138,
+      "eval_runtime": 44.1843,
+      "eval_samples_per_second": 22.632,
+      "eval_steps_per_second": 2.829,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 1.0464606285095215,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.0147,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 1.3230206966400146,
+      "eval_runtime": 44.0559,
+      "eval_samples_per_second": 22.698,
+      "eval_steps_per_second": 2.837,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 1.1091907024383545,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.0073,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 1.3765190839767456,
+      "eval_runtime": 44.0219,
+      "eval_samples_per_second": 22.716,
+      "eval_steps_per_second": 2.839,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 1.3128504753112793,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.0126,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 1.3743306398391724,
+      "eval_runtime": 43.9063,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 1.2510898113250732,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 0.9869,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 1.3918826580047607,
+      "eval_runtime": 43.9264,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 1.3030422925949097,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 0.9687,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 1.39524245262146,
+      "eval_runtime": 43.9233,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 1.395313024520874,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 0.9716,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 1.384624719619751,
+      "eval_runtime": 43.9592,
+      "eval_samples_per_second": 22.748,
+      "eval_steps_per_second": 2.844,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 1.5399748086929321,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 0.9585,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 1.3930742740631104,
+      "eval_runtime": 43.9163,
+      "eval_samples_per_second": 22.771,
+      "eval_steps_per_second": 2.846,
+      "step": 430
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 7.04601095405568e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-440/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-440/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-440/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-440/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-440/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-440/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-440/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-440/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..dc88b3ebd08a44a01b9d5a78a41ade9e49589e75
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-440/trainer_state.json
@@ -0,0 +1,693 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 5.866666666666667,
+  "eval_steps": 10,
+  "global_step": 440,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 0.9267418384552002,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.0599,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.324584722518921,
+      "eval_runtime": 43.853,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 1.116028070449829,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.0048,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 1.3211394548416138,
+      "eval_runtime": 44.1843,
+      "eval_samples_per_second": 22.632,
+      "eval_steps_per_second": 2.829,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 1.0464606285095215,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.0147,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 1.3230206966400146,
+      "eval_runtime": 44.0559,
+      "eval_samples_per_second": 22.698,
+      "eval_steps_per_second": 2.837,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 1.1091907024383545,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.0073,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 1.3765190839767456,
+      "eval_runtime": 44.0219,
+      "eval_samples_per_second": 22.716,
+      "eval_steps_per_second": 2.839,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 1.3128504753112793,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.0126,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 1.3743306398391724,
+      "eval_runtime": 43.9063,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 1.2510898113250732,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 0.9869,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 1.3918826580047607,
+      "eval_runtime": 43.9264,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 1.3030422925949097,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 0.9687,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 1.39524245262146,
+      "eval_runtime": 43.9233,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 1.395313024520874,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 0.9716,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 1.384624719619751,
+      "eval_runtime": 43.9592,
+      "eval_samples_per_second": 22.748,
+      "eval_steps_per_second": 2.844,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 1.5399748086929321,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 0.9585,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 1.3930742740631104,
+      "eval_runtime": 43.9163,
+      "eval_samples_per_second": 22.771,
+      "eval_steps_per_second": 2.846,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 1.2355530261993408,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 0.964,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 1.3807975053787231,
+      "eval_runtime": 43.8712,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 440
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 7.20987167391744e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-450/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-450/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-450/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-450/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-450/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-450/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-450/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-450/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..8e588a0c3953c6bf99fbcfc4f7fdf1d778e78ed9
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-450/trainer_state.json
@@ -0,0 +1,708 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 6.0,
+  "eval_steps": 10,
+  "global_step": 450,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 0.9267418384552002,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.0599,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.324584722518921,
+      "eval_runtime": 43.853,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 1.116028070449829,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.0048,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 1.3211394548416138,
+      "eval_runtime": 44.1843,
+      "eval_samples_per_second": 22.632,
+      "eval_steps_per_second": 2.829,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 1.0464606285095215,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.0147,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 1.3230206966400146,
+      "eval_runtime": 44.0559,
+      "eval_samples_per_second": 22.698,
+      "eval_steps_per_second": 2.837,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 1.1091907024383545,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.0073,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 1.3765190839767456,
+      "eval_runtime": 44.0219,
+      "eval_samples_per_second": 22.716,
+      "eval_steps_per_second": 2.839,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 1.3128504753112793,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.0126,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 1.3743306398391724,
+      "eval_runtime": 43.9063,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 1.2510898113250732,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 0.9869,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 1.3918826580047607,
+      "eval_runtime": 43.9264,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 1.3030422925949097,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 0.9687,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 1.39524245262146,
+      "eval_runtime": 43.9233,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 1.395313024520874,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 0.9716,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 1.384624719619751,
+      "eval_runtime": 43.9592,
+      "eval_samples_per_second": 22.748,
+      "eval_steps_per_second": 2.844,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 1.5399748086929321,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 0.9585,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 1.3930742740631104,
+      "eval_runtime": 43.9163,
+      "eval_samples_per_second": 22.771,
+      "eval_steps_per_second": 2.846,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 1.2355530261993408,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 0.964,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 1.3807975053787231,
+      "eval_runtime": 43.8712,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 1.3280516862869263,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 0.9691,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 1.3900312185287476,
+      "eval_runtime": 43.8794,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 450
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 7.3737323937792e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-460/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-460/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-460/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-460/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-460/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-460/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-460/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-460/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..351b967e75a5f6210efc0765244f77eac0b4d5e9
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-460/trainer_state.json
@@ -0,0 +1,723 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 6.133333333333334,
+  "eval_steps": 10,
+  "global_step": 460,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 0.9267418384552002,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.0599,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.324584722518921,
+      "eval_runtime": 43.853,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 1.116028070449829,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.0048,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 1.3211394548416138,
+      "eval_runtime": 44.1843,
+      "eval_samples_per_second": 22.632,
+      "eval_steps_per_second": 2.829,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 1.0464606285095215,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.0147,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 1.3230206966400146,
+      "eval_runtime": 44.0559,
+      "eval_samples_per_second": 22.698,
+      "eval_steps_per_second": 2.837,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 1.1091907024383545,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.0073,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 1.3765190839767456,
+      "eval_runtime": 44.0219,
+      "eval_samples_per_second": 22.716,
+      "eval_steps_per_second": 2.839,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 1.3128504753112793,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.0126,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 1.3743306398391724,
+      "eval_runtime": 43.9063,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 1.2510898113250732,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 0.9869,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 1.3918826580047607,
+      "eval_runtime": 43.9264,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 1.3030422925949097,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 0.9687,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 1.39524245262146,
+      "eval_runtime": 43.9233,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 1.395313024520874,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 0.9716,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 1.384624719619751,
+      "eval_runtime": 43.9592,
+      "eval_samples_per_second": 22.748,
+      "eval_steps_per_second": 2.844,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 1.5399748086929321,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 0.9585,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 1.3930742740631104,
+      "eval_runtime": 43.9163,
+      "eval_samples_per_second": 22.771,
+      "eval_steps_per_second": 2.846,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 1.2355530261993408,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 0.964,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 1.3807975053787231,
+      "eval_runtime": 43.8712,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 1.3280516862869263,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 0.9691,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 1.3900312185287476,
+      "eval_runtime": 43.8794,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 1.7928528785705566,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 0.9234,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 1.456609845161438,
+      "eval_runtime": 43.8602,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 7.53759311364096e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-470/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-470/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-470/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-470/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-470/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-470/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-470/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-470/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..de1487d95aad15472f5eaf3f4a70408c48fe1a35
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-470/trainer_state.json
@@ -0,0 +1,738 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 6.266666666666667,
+  "eval_steps": 10,
+  "global_step": 470,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 0.9267418384552002,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.0599,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.324584722518921,
+      "eval_runtime": 43.853,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 1.116028070449829,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.0048,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 1.3211394548416138,
+      "eval_runtime": 44.1843,
+      "eval_samples_per_second": 22.632,
+      "eval_steps_per_second": 2.829,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 1.0464606285095215,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.0147,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 1.3230206966400146,
+      "eval_runtime": 44.0559,
+      "eval_samples_per_second": 22.698,
+      "eval_steps_per_second": 2.837,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 1.1091907024383545,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.0073,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 1.3765190839767456,
+      "eval_runtime": 44.0219,
+      "eval_samples_per_second": 22.716,
+      "eval_steps_per_second": 2.839,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 1.3128504753112793,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.0126,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 1.3743306398391724,
+      "eval_runtime": 43.9063,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 1.2510898113250732,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 0.9869,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 1.3918826580047607,
+      "eval_runtime": 43.9264,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 1.3030422925949097,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 0.9687,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 1.39524245262146,
+      "eval_runtime": 43.9233,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 1.395313024520874,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 0.9716,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 1.384624719619751,
+      "eval_runtime": 43.9592,
+      "eval_samples_per_second": 22.748,
+      "eval_steps_per_second": 2.844,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 1.5399748086929321,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 0.9585,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 1.3930742740631104,
+      "eval_runtime": 43.9163,
+      "eval_samples_per_second": 22.771,
+      "eval_steps_per_second": 2.846,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 1.2355530261993408,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 0.964,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 1.3807975053787231,
+      "eval_runtime": 43.8712,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 1.3280516862869263,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 0.9691,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 1.3900312185287476,
+      "eval_runtime": 43.8794,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 1.7928528785705566,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 0.9234,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 1.456609845161438,
+      "eval_runtime": 43.8602,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    },
+    {
+      "epoch": 6.266666666666667,
+      "grad_norm": 1.4366625547409058,
+      "learning_rate": 2.4296296296296298e-05,
+      "loss": 0.9163,
+      "step": 470
+    },
+    {
+      "epoch": 6.266666666666667,
+      "eval_loss": 1.4368970394134521,
+      "eval_runtime": 43.8767,
+      "eval_samples_per_second": 22.791,
+      "eval_steps_per_second": 2.849,
+      "step": 470
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 7.70145383350272e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-480/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-480/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-480/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-480/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-480/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-480/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-480/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-480/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..9b6e7e309933d294cb3900f4aa5551f8f6cb080c
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-480/trainer_state.json
@@ -0,0 +1,753 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 6.4,
+  "eval_steps": 10,
+  "global_step": 480,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 0.9267418384552002,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.0599,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.324584722518921,
+      "eval_runtime": 43.853,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 1.116028070449829,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.0048,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 1.3211394548416138,
+      "eval_runtime": 44.1843,
+      "eval_samples_per_second": 22.632,
+      "eval_steps_per_second": 2.829,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 1.0464606285095215,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.0147,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 1.3230206966400146,
+      "eval_runtime": 44.0559,
+      "eval_samples_per_second": 22.698,
+      "eval_steps_per_second": 2.837,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 1.1091907024383545,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.0073,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 1.3765190839767456,
+      "eval_runtime": 44.0219,
+      "eval_samples_per_second": 22.716,
+      "eval_steps_per_second": 2.839,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 1.3128504753112793,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.0126,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 1.3743306398391724,
+      "eval_runtime": 43.9063,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 1.2510898113250732,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 0.9869,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 1.3918826580047607,
+      "eval_runtime": 43.9264,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 1.3030422925949097,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 0.9687,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 1.39524245262146,
+      "eval_runtime": 43.9233,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 1.395313024520874,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 0.9716,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 1.384624719619751,
+      "eval_runtime": 43.9592,
+      "eval_samples_per_second": 22.748,
+      "eval_steps_per_second": 2.844,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 1.5399748086929321,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 0.9585,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 1.3930742740631104,
+      "eval_runtime": 43.9163,
+      "eval_samples_per_second": 22.771,
+      "eval_steps_per_second": 2.846,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 1.2355530261993408,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 0.964,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 1.3807975053787231,
+      "eval_runtime": 43.8712,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 1.3280516862869263,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 0.9691,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 1.3900312185287476,
+      "eval_runtime": 43.8794,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 1.7928528785705566,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 0.9234,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 1.456609845161438,
+      "eval_runtime": 43.8602,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    },
+    {
+      "epoch": 6.266666666666667,
+      "grad_norm": 1.4366625547409058,
+      "learning_rate": 2.4296296296296298e-05,
+      "loss": 0.9163,
+      "step": 470
+    },
+    {
+      "epoch": 6.266666666666667,
+      "eval_loss": 1.4368970394134521,
+      "eval_runtime": 43.8767,
+      "eval_samples_per_second": 22.791,
+      "eval_steps_per_second": 2.849,
+      "step": 470
+    },
+    {
+      "epoch": 6.4,
+      "grad_norm": 1.487023949623108,
+      "learning_rate": 2.3111111111111112e-05,
+      "loss": 0.9004,
+      "step": 480
+    },
+    {
+      "epoch": 6.4,
+      "eval_loss": 1.4485058784484863,
+      "eval_runtime": 43.8559,
+      "eval_samples_per_second": 22.802,
+      "eval_steps_per_second": 2.85,
+      "step": 480
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 7.86531455336448e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-490/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-490/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-490/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-490/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-490/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-490/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-490/trainer_state.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-490/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..265af84795816bf4e607eea6f04c5ac63ede40b9
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-490/trainer_state.json
@@ -0,0 +1,768 @@
+{
+  "best_metric": 1.2202378511428833,
+  "best_model_checkpoint": "./output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-70",
+  "epoch": 6.533333333333333,
+  "eval_steps": 10,
+  "global_step": 490,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.30893075466156006,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.1733,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.2328641414642334,
+      "eval_runtime": 44.0263,
+      "eval_samples_per_second": 22.714,
+      "eval_steps_per_second": 2.839,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.17991244792938232,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.2254,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.228402853012085,
+      "eval_runtime": 43.8933,
+      "eval_samples_per_second": 22.783,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.1784493625164032,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.2043,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.2251635789871216,
+      "eval_runtime": 44.0062,
+      "eval_samples_per_second": 22.724,
+      "eval_steps_per_second": 2.841,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.21547502279281616,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.1879,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.2234975099563599,
+      "eval_runtime": 44.0274,
+      "eval_samples_per_second": 22.713,
+      "eval_steps_per_second": 2.839,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.22946320474147797,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.2158,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.2221243381500244,
+      "eval_runtime": 44.1867,
+      "eval_samples_per_second": 22.631,
+      "eval_steps_per_second": 2.829,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.23243005573749542,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.1901,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.220987319946289,
+      "eval_runtime": 44.0985,
+      "eval_samples_per_second": 22.677,
+      "eval_steps_per_second": 2.835,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.19336333870887756,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.2074,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.2202378511428833,
+      "eval_runtime": 43.9577,
+      "eval_samples_per_second": 22.749,
+      "eval_steps_per_second": 2.844,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.1610746681690216,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.1434,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.22028386592865,
+      "eval_runtime": 43.903,
+      "eval_samples_per_second": 22.777,
+      "eval_steps_per_second": 2.847,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.18507854640483856,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.1506,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.221218466758728,
+      "eval_runtime": 43.981,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.17022280395030975,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.1761,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.2210596799850464,
+      "eval_runtime": 43.9473,
+      "eval_samples_per_second": 22.755,
+      "eval_steps_per_second": 2.844,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.27772682905197144,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.2465,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.2218444347381592,
+      "eval_runtime": 43.8733,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.2792418599128723,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.1664,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.2227915525436401,
+      "eval_runtime": 43.869,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.32393139600753784,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.1835,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.2218685150146484,
+      "eval_runtime": 43.878,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.3198949694633484,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.1687,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.2223820686340332,
+      "eval_runtime": 43.9319,
+      "eval_samples_per_second": 22.763,
+      "eval_steps_per_second": 2.845,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.2342524528503418,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.1516,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.2233225107192993,
+      "eval_runtime": 43.9266,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.26675984263420105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.1673,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.2325456142425537,
+      "eval_runtime": 43.9006,
+      "eval_samples_per_second": 22.779,
+      "eval_steps_per_second": 2.847,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 0.36160191893577576,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.1959,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.2345908880233765,
+      "eval_runtime": 44.0473,
+      "eval_samples_per_second": 22.703,
+      "eval_steps_per_second": 2.838,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.35918164253234863,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.1213,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.2354995012283325,
+      "eval_runtime": 43.984,
+      "eval_samples_per_second": 22.736,
+      "eval_steps_per_second": 2.842,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 0.4165070652961731,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.1228,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.2382323741912842,
+      "eval_runtime": 44.1465,
+      "eval_samples_per_second": 22.652,
+      "eval_steps_per_second": 2.831,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.3703323304653168,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.1306,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.2381049394607544,
+      "eval_runtime": 44.0824,
+      "eval_samples_per_second": 22.685,
+      "eval_steps_per_second": 2.836,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 0.49251970648765564,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.1196,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.2419582605361938,
+      "eval_runtime": 44.1478,
+      "eval_samples_per_second": 22.651,
+      "eval_steps_per_second": 2.831,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 0.5216273069381714,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.1375,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.2372699975967407,
+      "eval_runtime": 44.195,
+      "eval_samples_per_second": 22.627,
+      "eval_steps_per_second": 2.828,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 0.4238261580467224,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.1573,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.2556878328323364,
+      "eval_runtime": 44.2342,
+      "eval_samples_per_second": 22.607,
+      "eval_steps_per_second": 2.826,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.72156822681427,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.0865,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.2621344327926636,
+      "eval_runtime": 44.2027,
+      "eval_samples_per_second": 22.623,
+      "eval_steps_per_second": 2.828,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.5642262101173401,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.0993,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.2770243883132935,
+      "eval_runtime": 44.0511,
+      "eval_samples_per_second": 22.701,
+      "eval_steps_per_second": 2.838,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 0.7814852595329285,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.0989,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.2699764966964722,
+      "eval_runtime": 44.1962,
+      "eval_samples_per_second": 22.626,
+      "eval_steps_per_second": 2.828,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 0.698136031627655,
+      "learning_rate": 4.8e-05,
+      "loss": 1.1381,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.2810109853744507,
+      "eval_runtime": 44.084,
+      "eval_samples_per_second": 22.684,
+      "eval_steps_per_second": 2.835,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 0.6332135796546936,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.0574,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.2708227634429932,
+      "eval_runtime": 43.9939,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 0.9241636991500854,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.0944,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.2758972644805908,
+      "eval_runtime": 43.9816,
+      "eval_samples_per_second": 22.737,
+      "eval_steps_per_second": 2.842,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.639854371547699,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.0468,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.271722674369812,
+      "eval_runtime": 44.0382,
+      "eval_samples_per_second": 22.708,
+      "eval_steps_per_second": 2.838,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.184584140777588,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.036,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.3531861305236816,
+      "eval_runtime": 44.1195,
+      "eval_samples_per_second": 22.666,
+      "eval_steps_per_second": 2.833,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 0.9589372873306274,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.0382,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.3156057596206665,
+      "eval_runtime": 43.996,
+      "eval_samples_per_second": 22.729,
+      "eval_steps_per_second": 2.841,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.099959135055542,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.0621,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.3207496404647827,
+      "eval_runtime": 44.0529,
+      "eval_samples_per_second": 22.7,
+      "eval_steps_per_second": 2.837,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 1.2086342573165894,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.0585,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.3306328058242798,
+      "eval_runtime": 43.8749,
+      "eval_samples_per_second": 22.792,
+      "eval_steps_per_second": 2.849,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 0.9267418384552002,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.0599,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.324584722518921,
+      "eval_runtime": 43.853,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 1.116028070449829,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.0048,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 1.3211394548416138,
+      "eval_runtime": 44.1843,
+      "eval_samples_per_second": 22.632,
+      "eval_steps_per_second": 2.829,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 1.0464606285095215,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.0147,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 1.3230206966400146,
+      "eval_runtime": 44.0559,
+      "eval_samples_per_second": 22.698,
+      "eval_steps_per_second": 2.837,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 1.1091907024383545,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.0073,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 1.3765190839767456,
+      "eval_runtime": 44.0219,
+      "eval_samples_per_second": 22.716,
+      "eval_steps_per_second": 2.839,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 1.3128504753112793,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.0126,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 1.3743306398391724,
+      "eval_runtime": 43.9063,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 1.2510898113250732,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 0.9869,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 1.3918826580047607,
+      "eval_runtime": 43.9264,
+      "eval_samples_per_second": 22.765,
+      "eval_steps_per_second": 2.846,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 1.3030422925949097,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 0.9687,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 1.39524245262146,
+      "eval_runtime": 43.9233,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 1.395313024520874,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 0.9716,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 1.384624719619751,
+      "eval_runtime": 43.9592,
+      "eval_samples_per_second": 22.748,
+      "eval_steps_per_second": 2.844,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 1.5399748086929321,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 0.9585,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 1.3930742740631104,
+      "eval_runtime": 43.9163,
+      "eval_samples_per_second": 22.771,
+      "eval_steps_per_second": 2.846,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 1.2355530261993408,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 0.964,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 1.3807975053787231,
+      "eval_runtime": 43.8712,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 1.3280516862869263,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 0.9691,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 1.3900312185287476,
+      "eval_runtime": 43.8794,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 1.7928528785705566,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 0.9234,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 1.456609845161438,
+      "eval_runtime": 43.8602,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    },
+    {
+      "epoch": 6.266666666666667,
+      "grad_norm": 1.4366625547409058,
+      "learning_rate": 2.4296296296296298e-05,
+      "loss": 0.9163,
+      "step": 470
+    },
+    {
+      "epoch": 6.266666666666667,
+      "eval_loss": 1.4368970394134521,
+      "eval_runtime": 43.8767,
+      "eval_samples_per_second": 22.791,
+      "eval_steps_per_second": 2.849,
+      "step": 470
+    },
+    {
+      "epoch": 6.4,
+      "grad_norm": 1.487023949623108,
+      "learning_rate": 2.3111111111111112e-05,
+      "loss": 0.9004,
+      "step": 480
+    },
+    {
+      "epoch": 6.4,
+      "eval_loss": 1.4485058784484863,
+      "eval_runtime": 43.8559,
+      "eval_samples_per_second": 22.802,
+      "eval_steps_per_second": 2.85,
+      "step": 480
+    },
+    {
+      "epoch": 6.533333333333333,
+      "grad_norm": 1.6088396310806274,
+      "learning_rate": 2.192592592592593e-05,
+      "loss": 0.9237,
+      "step": 490
+    },
+    {
+      "epoch": 6.533333333333333,
+      "eval_loss": 1.4380258321762085,
+      "eval_runtime": 43.8588,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 490
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 8.02917527322624e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-500/README.md b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-500/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-500/README.md
@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2
\ No newline at end of file
diff --git a/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-500/adapter_config.json b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-500/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c21151c317f8c6bb2b078291858dfb0ec6b1997f
--- /dev/null
+++ b/output_ft_more_layers_math_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-math-8e-05/checkpoint-500/adapter_config.json
@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense_h_to_4h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_opensubtitles_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-opensubtitles-8e-05/checkpoint-360/adapter_model.safetensors b/output_ft_more_layers_opensubtitles_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-opensubtitles-8e-05/checkpoint-360/adapter_model.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..aa4c52d83343aefefcbf7ab411a5b6f706a3c83b
--- /dev/null
+++ b/output_ft_more_layers_opensubtitles_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-opensubtitles-8e-05/checkpoint-360/adapter_model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:423f10178e9f0f59e2a45c4dd59ea412bbae3650165092a37eca70a2072744e1
+size 67144544
diff --git a/output_ft_more_layers_stackexchange_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-stackexchange-8e-05/checkpoint-410/rng_state.pth b/output_ft_more_layers_stackexchange_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-stackexchange-8e-05/checkpoint-410/rng_state.pth
new file mode 100644
index 0000000000000000000000000000000000000000..090a1de878697aa3e6255ed23ff26ce6e561a9fa
--- /dev/null
+++ b/output_ft_more_layers_stackexchange_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-stackexchange-8e-05/checkpoint-410/rng_state.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2cab01f3c0a9d66cf16eec91d8aebbfd533628e45bdb849b4c3e4ad317f15270
+size 14575
diff --git a/output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-660/adapter_model.safetensors b/output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-660/adapter_model.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..6203e4e31d8830e071081c8871c33d47860b8a18
--- /dev/null
+++ b/output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-660/adapter_model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dfee8ba5c4025a77597853a66f879a2da268a3e3289db1537050ab31db12e77f
+size 67144544
diff --git a/output_ft_more_layers_uspto_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-uspto-8e-05/checkpoint-300/rng_state.pth b/output_ft_more_layers_uspto_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-uspto-8e-05/checkpoint-300/rng_state.pth
new file mode 100644
index 0000000000000000000000000000000000000000..4d8ba268ef07796e970a23442889935701a1dda5
--- /dev/null
+++ b/output_ft_more_layers_uspto_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-uspto-8e-05/checkpoint-300/rng_state.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2574c6149307e492ef05d2031918a546356cc654f4671c817f05ae6d0764de7f
+size 14575