diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-110/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-110/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..1ee54189141f6d5e57c1dce6408da63681a6acca
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-110/trainer_state.json
@@ -0,0 +1,198 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "epoch": 1.4666666666666668,
+  "eval_steps": 10,
+  "global_step": 110,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    }
+  ],
+  "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": 1.80246791847936e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-120/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-120/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-120/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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-120/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-120/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-120/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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-120/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-120/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..c7ac0b3c5ed5ec4aef4e24403a049d6973509208
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-120/trainer_state.json
@@ -0,0 +1,213 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "epoch": 1.6,
+  "eval_steps": 10,
+  "global_step": 120,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    }
+  ],
+  "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": 1.96632863834112e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-130/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-130/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-130/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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-130/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-130/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-130/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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-130/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-130/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..a20f6b5f64c0089e145bfe433d9c4dd6efed39a4
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-130/trainer_state.json
@@ -0,0 +1,228 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "epoch": 1.7333333333333334,
+  "eval_steps": 10,
+  "global_step": 130,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    }
+  ],
+  "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": 2.13018935820288e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-140/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-140/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-140/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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-140/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-140/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-140/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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-140/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-140/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..2faa4fe5da63d1683f9d379b06774689725d7bce
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-140/trainer_state.json
@@ -0,0 +1,243 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "epoch": 1.8666666666666667,
+  "eval_steps": 10,
+  "global_step": 140,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    }
+  ],
+  "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": 2.29405007806464e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-150/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-150/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-150/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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-150/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-150/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-150/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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-150/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-150/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..b2fdb0d061c5aea91ac0d6f40e40858524997b94
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-150/trainer_state.json
@@ -0,0 +1,258 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "epoch": 2.0,
+  "eval_steps": 10,
+  "global_step": 150,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    }
+  ],
+  "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": 2.4579107979264e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-160/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-160/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-160/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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-160/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-160/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-160/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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-160/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-160/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..337ce2e0e60e6e91f0caab99b63b573bace83d1e
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-160/trainer_state.json
@@ -0,0 +1,273 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "epoch": 2.1333333333333333,
+  "eval_steps": 10,
+  "global_step": 160,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    }
+  ],
+  "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": 2.62177151778816e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-170/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-170/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-170/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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-170/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-170/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-170/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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-170/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-170/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..0255b39e02c6283774f5496364f4ef0423de2223
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-170/trainer_state.json
@@ -0,0 +1,288 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "epoch": 2.2666666666666666,
+  "eval_steps": 10,
+  "global_step": 170,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    }
+  ],
+  "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": 2.78563223764992e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-180/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-180/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-180/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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-180/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-180/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-180/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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-180/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-180/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..90a7b901e6d886ed9a66cbc875b3ba9486de9af8
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-180/trainer_state.json
@@ -0,0 +1,303 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "epoch": 2.4,
+  "eval_steps": 10,
+  "global_step": 180,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    }
+  ],
+  "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": 2.94949295751168e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-190/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-190/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-190/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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-190/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-190/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-190/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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-190/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-190/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..b330fa2254e8d4208c35ecd1b42b43ca8d9fd19f
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-190/trainer_state.json
@@ -0,0 +1,318 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "epoch": 2.533333333333333,
+  "eval_steps": 10,
+  "global_step": 190,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    }
+  ],
+  "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": 3.11335367737344e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-200/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-200/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-200/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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-200/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-200/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-200/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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-200/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-200/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..603356b8dc6c37cc54e774cb44ff21f76f565d9d
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-200/trainer_state.json
@@ -0,0 +1,333 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "epoch": 2.6666666666666665,
+  "eval_steps": 10,
+  "global_step": 200,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    }
+  ],
+  "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": 3.2772143972352e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-210/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-210/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-210/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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-210/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-210/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-210/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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-210/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-210/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..9bffae6fced9191c68eb8db55e616b83ce314c2a
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-210/trainer_state.json
@@ -0,0 +1,348 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "epoch": 2.8,
+  "eval_steps": 10,
+  "global_step": 210,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1638202667236328,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.5345,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.8096415996551514,
+      "eval_runtime": 43.8206,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 210
+    }
+  ],
+  "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": 3.44107511709696e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-220/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-220/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-220/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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-220/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-220/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-220/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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-220/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-220/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..6ae1642b1ae166ad651cd33569c7a6990a92bc43
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-220/trainer_state.json
@@ -0,0 +1,363 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "epoch": 2.9333333333333336,
+  "eval_steps": 10,
+  "global_step": 220,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1638202667236328,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.5345,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.8096415996551514,
+      "eval_runtime": 43.8206,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.2765487432479858,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.6074,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.810752034187317,
+      "eval_runtime": 43.8178,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 220
+    }
+  ],
+  "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": 3.60493583695872e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-230/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-230/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-230/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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-230/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-230/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-230/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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-230/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-230/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..278c6d37e87b3216273bf457cfa5cfcccc91961f
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-230/trainer_state.json
@@ -0,0 +1,378 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "epoch": 3.066666666666667,
+  "eval_steps": 10,
+  "global_step": 230,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1638202667236328,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.5345,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.8096415996551514,
+      "eval_runtime": 43.8206,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.2765487432479858,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.6074,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.810752034187317,
+      "eval_runtime": 43.8178,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.4451857805252075,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.5139,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.8353334665298462,
+      "eval_runtime": 43.831,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 230
+    }
+  ],
+  "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": 3.76879655682048e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-240/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-240/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-240/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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-240/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-240/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-240/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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-240/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-240/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..26cf6898101de0ece545e01694865ecd5fdf57ec
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-240/trainer_state.json
@@ -0,0 +1,393 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "epoch": 3.2,
+  "eval_steps": 10,
+  "global_step": 240,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1638202667236328,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.5345,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.8096415996551514,
+      "eval_runtime": 43.8206,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.2765487432479858,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.6074,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.810752034187317,
+      "eval_runtime": 43.8178,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.4451857805252075,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.5139,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.8353334665298462,
+      "eval_runtime": 43.831,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 1.697195291519165,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.3564,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.8831367492675781,
+      "eval_runtime": 43.8285,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 240
+    }
+  ],
+  "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": 3.93265727668224e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-250/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-250/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-250/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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-250/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-250/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-250/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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-250/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-250/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..d260e6903ef7b7b1ebb8f8854796f6aba31f34ce
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-250/trainer_state.json
@@ -0,0 +1,408 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "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": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1638202667236328,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.5345,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.8096415996551514,
+      "eval_runtime": 43.8206,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.2765487432479858,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.6074,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.810752034187317,
+      "eval_runtime": 43.8178,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.4451857805252075,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.5139,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.8353334665298462,
+      "eval_runtime": 43.831,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 1.697195291519165,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.3564,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.8831367492675781,
+      "eval_runtime": 43.8285,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.650194525718689,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.3952,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.8923019170761108,
+      "eval_runtime": 43.8237,
+      "eval_samples_per_second": 22.819,
+      "eval_steps_per_second": 2.852,
+      "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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-260/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-260/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-260/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-260/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-260/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-260/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..19ac06f92a0be97d759bc0405c05231633309db1
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-260/trainer_state.json
@@ -0,0 +1,423 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "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": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1638202667236328,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.5345,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.8096415996551514,
+      "eval_runtime": 43.8206,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.2765487432479858,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.6074,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.810752034187317,
+      "eval_runtime": 43.8178,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.4451857805252075,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.5139,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.8353334665298462,
+      "eval_runtime": 43.831,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 1.697195291519165,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.3564,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.8831367492675781,
+      "eval_runtime": 43.8285,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.650194525718689,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.3952,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.8923019170761108,
+      "eval_runtime": 43.8237,
+      "eval_samples_per_second": 22.819,
+      "eval_steps_per_second": 2.852,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 1.7771501541137695,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.2664,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.8947919607162476,
+      "eval_runtime": 43.851,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-270/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-270/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-270/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-270/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-270/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-270/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..862a16ed0698a1f13ce5f40da960349f5a80769f
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-270/trainer_state.json
@@ -0,0 +1,438 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "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": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1638202667236328,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.5345,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.8096415996551514,
+      "eval_runtime": 43.8206,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.2765487432479858,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.6074,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.810752034187317,
+      "eval_runtime": 43.8178,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.4451857805252075,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.5139,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.8353334665298462,
+      "eval_runtime": 43.831,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 1.697195291519165,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.3564,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.8831367492675781,
+      "eval_runtime": 43.8285,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.650194525718689,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.3952,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.8923019170761108,
+      "eval_runtime": 43.8237,
+      "eval_samples_per_second": 22.819,
+      "eval_steps_per_second": 2.852,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 1.7771501541137695,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.2664,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.8947919607162476,
+      "eval_runtime": 43.851,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 1.5858917236328125,
+      "learning_rate": 4.8e-05,
+      "loss": 1.4785,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.8847408294677734,
+      "eval_runtime": 43.8427,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-280/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-280/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-280/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-280/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-280/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-280/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..5ee3e8e79b366ab51cd5a339bb829b75f3396018
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-280/trainer_state.json
@@ -0,0 +1,453 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "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": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1638202667236328,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.5345,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.8096415996551514,
+      "eval_runtime": 43.8206,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.2765487432479858,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.6074,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.810752034187317,
+      "eval_runtime": 43.8178,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.4451857805252075,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.5139,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.8353334665298462,
+      "eval_runtime": 43.831,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 1.697195291519165,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.3564,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.8831367492675781,
+      "eval_runtime": 43.8285,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.650194525718689,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.3952,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.8923019170761108,
+      "eval_runtime": 43.8237,
+      "eval_samples_per_second": 22.819,
+      "eval_steps_per_second": 2.852,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 1.7771501541137695,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.2664,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.8947919607162476,
+      "eval_runtime": 43.851,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 1.5858917236328125,
+      "learning_rate": 4.8e-05,
+      "loss": 1.4785,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.8847408294677734,
+      "eval_runtime": 43.8427,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 1.738616704940796,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.4324,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.8960140943527222,
+      "eval_runtime": 43.844,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-290/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-290/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-290/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-290/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-290/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-290/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..b0a6cfe972288b10f75dd3f2a05f921cbe46ae25
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-290/trainer_state.json
@@ -0,0 +1,468 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "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": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1638202667236328,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.5345,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.8096415996551514,
+      "eval_runtime": 43.8206,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.2765487432479858,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.6074,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.810752034187317,
+      "eval_runtime": 43.8178,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.4451857805252075,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.5139,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.8353334665298462,
+      "eval_runtime": 43.831,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 1.697195291519165,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.3564,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.8831367492675781,
+      "eval_runtime": 43.8285,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.650194525718689,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.3952,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.8923019170761108,
+      "eval_runtime": 43.8237,
+      "eval_samples_per_second": 22.819,
+      "eval_steps_per_second": 2.852,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 1.7771501541137695,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.2664,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.8947919607162476,
+      "eval_runtime": 43.851,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 1.5858917236328125,
+      "learning_rate": 4.8e-05,
+      "loss": 1.4785,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.8847408294677734,
+      "eval_runtime": 43.8427,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 1.738616704940796,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.4324,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.8960140943527222,
+      "eval_runtime": 43.844,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 1.6031432151794434,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.4623,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.8914765119552612,
+      "eval_runtime": 43.8505,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-300/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-300/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-300/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-300/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-300/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-300/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..4628bd6d7cbd1025449b155e7b83dff436392e40
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-300/trainer_state.json
@@ -0,0 +1,483 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "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": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1638202667236328,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.5345,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.8096415996551514,
+      "eval_runtime": 43.8206,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.2765487432479858,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.6074,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.810752034187317,
+      "eval_runtime": 43.8178,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.4451857805252075,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.5139,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.8353334665298462,
+      "eval_runtime": 43.831,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 1.697195291519165,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.3564,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.8831367492675781,
+      "eval_runtime": 43.8285,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.650194525718689,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.3952,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.8923019170761108,
+      "eval_runtime": 43.8237,
+      "eval_samples_per_second": 22.819,
+      "eval_steps_per_second": 2.852,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 1.7771501541137695,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.2664,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.8947919607162476,
+      "eval_runtime": 43.851,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 1.5858917236328125,
+      "learning_rate": 4.8e-05,
+      "loss": 1.4785,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.8847408294677734,
+      "eval_runtime": 43.8427,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 1.738616704940796,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.4324,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.8960140943527222,
+      "eval_runtime": 43.844,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 1.6031432151794434,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.4623,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.8914765119552612,
+      "eval_runtime": 43.8505,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 1.683716893196106,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.3815,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.89323890209198,
+      "eval_runtime": 43.8304,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-310/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-310/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-310/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-310/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-310/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-310/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..6e7a5d5cb386a1f76b2d16e0808871664dcd822c
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-310/trainer_state.json
@@ -0,0 +1,498 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "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": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1638202667236328,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.5345,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.8096415996551514,
+      "eval_runtime": 43.8206,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.2765487432479858,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.6074,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.810752034187317,
+      "eval_runtime": 43.8178,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.4451857805252075,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.5139,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.8353334665298462,
+      "eval_runtime": 43.831,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 1.697195291519165,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.3564,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.8831367492675781,
+      "eval_runtime": 43.8285,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.650194525718689,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.3952,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.8923019170761108,
+      "eval_runtime": 43.8237,
+      "eval_samples_per_second": 22.819,
+      "eval_steps_per_second": 2.852,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 1.7771501541137695,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.2664,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.8947919607162476,
+      "eval_runtime": 43.851,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 1.5858917236328125,
+      "learning_rate": 4.8e-05,
+      "loss": 1.4785,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.8847408294677734,
+      "eval_runtime": 43.8427,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 1.738616704940796,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.4324,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.8960140943527222,
+      "eval_runtime": 43.844,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 1.6031432151794434,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.4623,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.8914765119552612,
+      "eval_runtime": 43.8505,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 1.683716893196106,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.3815,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.89323890209198,
+      "eval_runtime": 43.8304,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.832708477973938,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.2467,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.9707167148590088,
+      "eval_runtime": 43.8554,
+      "eval_samples_per_second": 22.802,
+      "eval_steps_per_second": 2.85,
+      "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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-320/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-320/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-320/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-320/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-320/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-320/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..9a9998c1a7002654abbda1084ddba7ad2d8d1364
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-320/trainer_state.json
@@ -0,0 +1,513 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "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": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1638202667236328,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.5345,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.8096415996551514,
+      "eval_runtime": 43.8206,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.2765487432479858,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.6074,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.810752034187317,
+      "eval_runtime": 43.8178,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.4451857805252075,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.5139,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.8353334665298462,
+      "eval_runtime": 43.831,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 1.697195291519165,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.3564,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.8831367492675781,
+      "eval_runtime": 43.8285,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.650194525718689,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.3952,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.8923019170761108,
+      "eval_runtime": 43.8237,
+      "eval_samples_per_second": 22.819,
+      "eval_steps_per_second": 2.852,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 1.7771501541137695,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.2664,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.8947919607162476,
+      "eval_runtime": 43.851,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 1.5858917236328125,
+      "learning_rate": 4.8e-05,
+      "loss": 1.4785,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.8847408294677734,
+      "eval_runtime": 43.8427,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 1.738616704940796,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.4324,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.8960140943527222,
+      "eval_runtime": 43.844,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 1.6031432151794434,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.4623,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.8914765119552612,
+      "eval_runtime": 43.8505,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 1.683716893196106,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.3815,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.89323890209198,
+      "eval_runtime": 43.8304,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.832708477973938,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.2467,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.9707167148590088,
+      "eval_runtime": 43.8554,
+      "eval_samples_per_second": 22.802,
+      "eval_steps_per_second": 2.85,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 1.9778881072998047,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.3088,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.980672836303711,
+      "eval_runtime": 43.8963,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-330/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-330/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-330/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-330/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-330/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-330/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..98802f40ad83ac6049b6eb3e11c9d03a47d1d652
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-330/trainer_state.json
@@ -0,0 +1,528 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "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": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1638202667236328,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.5345,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.8096415996551514,
+      "eval_runtime": 43.8206,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.2765487432479858,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.6074,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.810752034187317,
+      "eval_runtime": 43.8178,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.4451857805252075,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.5139,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.8353334665298462,
+      "eval_runtime": 43.831,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 1.697195291519165,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.3564,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.8831367492675781,
+      "eval_runtime": 43.8285,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.650194525718689,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.3952,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.8923019170761108,
+      "eval_runtime": 43.8237,
+      "eval_samples_per_second": 22.819,
+      "eval_steps_per_second": 2.852,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 1.7771501541137695,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.2664,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.8947919607162476,
+      "eval_runtime": 43.851,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 1.5858917236328125,
+      "learning_rate": 4.8e-05,
+      "loss": 1.4785,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.8847408294677734,
+      "eval_runtime": 43.8427,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 1.738616704940796,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.4324,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.8960140943527222,
+      "eval_runtime": 43.844,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 1.6031432151794434,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.4623,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.8914765119552612,
+      "eval_runtime": 43.8505,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 1.683716893196106,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.3815,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.89323890209198,
+      "eval_runtime": 43.8304,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.832708477973938,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.2467,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.9707167148590088,
+      "eval_runtime": 43.8554,
+      "eval_samples_per_second": 22.802,
+      "eval_steps_per_second": 2.85,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 1.9778881072998047,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.3088,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.980672836303711,
+      "eval_runtime": 43.8963,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.989790678024292,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.2894,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.9843915700912476,
+      "eval_runtime": 43.8339,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-340/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-340/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-340/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-340/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-340/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-340/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..40d46b43eb5f5ea089459fc104109275b97c3a63
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-340/trainer_state.json
@@ -0,0 +1,543 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "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": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1638202667236328,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.5345,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.8096415996551514,
+      "eval_runtime": 43.8206,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.2765487432479858,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.6074,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.810752034187317,
+      "eval_runtime": 43.8178,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.4451857805252075,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.5139,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.8353334665298462,
+      "eval_runtime": 43.831,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 1.697195291519165,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.3564,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.8831367492675781,
+      "eval_runtime": 43.8285,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.650194525718689,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.3952,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.8923019170761108,
+      "eval_runtime": 43.8237,
+      "eval_samples_per_second": 22.819,
+      "eval_steps_per_second": 2.852,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 1.7771501541137695,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.2664,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.8947919607162476,
+      "eval_runtime": 43.851,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 1.5858917236328125,
+      "learning_rate": 4.8e-05,
+      "loss": 1.4785,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.8847408294677734,
+      "eval_runtime": 43.8427,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 1.738616704940796,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.4324,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.8960140943527222,
+      "eval_runtime": 43.844,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 1.6031432151794434,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.4623,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.8914765119552612,
+      "eval_runtime": 43.8505,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 1.683716893196106,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.3815,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.89323890209198,
+      "eval_runtime": 43.8304,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.832708477973938,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.2467,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.9707167148590088,
+      "eval_runtime": 43.8554,
+      "eval_samples_per_second": 22.802,
+      "eval_steps_per_second": 2.85,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 1.9778881072998047,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.3088,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.980672836303711,
+      "eval_runtime": 43.8963,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.989790678024292,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.2894,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.9843915700912476,
+      "eval_runtime": 43.8339,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.0734732151031494,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.2478,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.9802476167678833,
+      "eval_runtime": 43.8578,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-350/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-350/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-350/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-350/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-350/trainer_state.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-350/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..5cf7393e3fdcf412aabe1fc3efd560592e3b19d2
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-350/trainer_state.json
@@ -0,0 +1,558 @@
+{
+  "best_metric": 1.7508132457733154,
+  "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
+  "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": 0.3951323926448822,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 1.8421,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 1.7700647115707397,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3800930380821228,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 1.7715,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 1.7666271924972534,
+      "eval_runtime": 43.8435,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3974359333515167,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 1.7799,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 1.7623893022537231,
+      "eval_runtime": 43.863,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.37877357006073,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 1.7416,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 1.7585530281066895,
+      "eval_runtime": 43.8506,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3691335618495941,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 1.754,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 1.7555732727050781,
+      "eval_runtime": 43.8591,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3394964337348938,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 1.639,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.7534734010696411,
+      "eval_runtime": 43.8608,
+      "eval_samples_per_second": 22.799,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.317234069108963,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 1.7729,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 1.7515993118286133,
+      "eval_runtime": 43.8388,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3309251666069031,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.8009,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 1.7508132457733154,
+      "eval_runtime": 43.8535,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.4126473367214203,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.6602,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 1.753326177597046,
+      "eval_runtime": 43.86,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.5640483498573303,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.5879,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 1.7581162452697754,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.6418269276618958,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.7067,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 1.7590935230255127,
+      "eval_runtime": 43.8372,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.603199303150177,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.7311,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 1.760871410369873,
+      "eval_runtime": 43.828,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.7207424640655518,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.7103,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 1.761257529258728,
+      "eval_runtime": 43.8422,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 0.6793868541717529,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 1.6574,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 1.7610187530517578,
+      "eval_runtime": 43.8261,
+      "eval_samples_per_second": 22.817,
+      "eval_steps_per_second": 2.852,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.7147842049598694,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 1.6357,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.763314962387085,
+      "eval_runtime": 43.8315,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 0.8159098625183105,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 1.62,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 1.7846354246139526,
+      "eval_runtime": 43.8212,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.0052918195724487,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 1.5109,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 1.8005082607269287,
+      "eval_runtime": 43.8314,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.089106559753418,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 1.5658,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 1.8088901042938232,
+      "eval_runtime": 43.8245,
+      "eval_samples_per_second": 22.818,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.1667160987854004,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 1.6316,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 1.8114306926727295,
+      "eval_runtime": 43.8195,
+      "eval_samples_per_second": 22.821,
+      "eval_steps_per_second": 2.853,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.215566873550415,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 1.4806,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 1.811687707901001,
+      "eval_runtime": 43.8494,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1638202667236328,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 1.5345,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 1.8096415996551514,
+      "eval_runtime": 43.8206,
+      "eval_samples_per_second": 22.82,
+      "eval_steps_per_second": 2.853,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.2765487432479858,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 1.6074,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 1.810752034187317,
+      "eval_runtime": 43.8178,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.4451857805252075,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 1.5139,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 1.8353334665298462,
+      "eval_runtime": 43.831,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 1.697195291519165,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 1.3564,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 1.8831367492675781,
+      "eval_runtime": 43.8285,
+      "eval_samples_per_second": 22.816,
+      "eval_steps_per_second": 2.852,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.650194525718689,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 1.3952,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 1.8923019170761108,
+      "eval_runtime": 43.8237,
+      "eval_samples_per_second": 22.819,
+      "eval_steps_per_second": 2.852,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 1.7771501541137695,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 1.2664,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 1.8947919607162476,
+      "eval_runtime": 43.851,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 1.5858917236328125,
+      "learning_rate": 4.8e-05,
+      "loss": 1.4785,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 1.8847408294677734,
+      "eval_runtime": 43.8427,
+      "eval_samples_per_second": 22.809,
+      "eval_steps_per_second": 2.851,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 1.738616704940796,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 1.4324,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 1.8960140943527222,
+      "eval_runtime": 43.844,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 1.6031432151794434,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 1.4623,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 1.8914765119552612,
+      "eval_runtime": 43.8505,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 1.683716893196106,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 1.3815,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.89323890209198,
+      "eval_runtime": 43.8304,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 1.832708477973938,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.2467,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 1.9707167148590088,
+      "eval_runtime": 43.8554,
+      "eval_samples_per_second": 22.802,
+      "eval_steps_per_second": 2.85,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 1.9778881072998047,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.3088,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 1.980672836303711,
+      "eval_runtime": 43.8963,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 1.989790678024292,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.2894,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 1.9843915700912476,
+      "eval_runtime": 43.8339,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.0734732151031494,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.2478,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 1.9802476167678833,
+      "eval_runtime": 43.8578,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 1.9041788578033447,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.2407,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 1.9780033826828003,
+      "eval_runtime": 43.9861,
+      "eval_samples_per_second": 22.734,
+      "eval_steps_per_second": 2.842,
+      "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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-360/README.md b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-360/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e255b1d99c1c1d12955d852dc1056813be7ffca0
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-360/adapter_config.json b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-360/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2dac7d45378cb5fa31de4db4886fb4f63ba5fcc9
--- /dev/null
+++ b/output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-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": [
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value",
+    "dense_h_to_4h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}
\ No newline at end of file
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/scheduler.pt 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/scheduler.pt
new file mode 100644
index 0000000000000000000000000000000000000000..3e7b4a9f9937960a244cecd26e39e2fa8d47c371
--- /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/scheduler.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2b689751bdfd06f9f14e988ce4878a3f9cc346d9a8ec3506deaf370cf05f29f4
+size 627
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-580/training_args.bin 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-580/training_args.bin
new file mode 100644
index 0000000000000000000000000000000000000000..68b02330a1195a7529b7c5ac3d2074dca7a8843d
--- /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-580/training_args.bin
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5276490505c682789e6f542349fd3b486cf3586ea6a988c79078113f82ac15c0
+size 4859
diff --git a/output_ft_more_layers_hackernews_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-hackernews-8e-05/checkpoint-320/training_args.bin b/output_ft_more_layers_hackernews_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-hackernews-8e-05/checkpoint-320/training_args.bin
new file mode 100644
index 0000000000000000000000000000000000000000..1b36d56f3e7bbd7abe2f26b35ff49f9f8148b671
--- /dev/null
+++ b/output_ft_more_layers_hackernews_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-hackernews-8e-05/checkpoint-320/training_args.bin
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cda8e41a408b45a7a6604c90cbebf2f8b1064d9750a6a2900ae126084a84e2d8
+size 4859
diff --git a/output_ft_more_layers_hackernews_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-hackernews-8e-05/checkpoint-650/optimizer.pt b/output_ft_more_layers_hackernews_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-hackernews-8e-05/checkpoint-650/optimizer.pt
new file mode 100644
index 0000000000000000000000000000000000000000..9b55503da3dcf4acb635f880956f2b8cf4cd0af6
--- /dev/null
+++ b/output_ft_more_layers_hackernews_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-hackernews-8e-05/checkpoint-650/optimizer.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:684dad9458aa64d44aeeb3fdaa85b72a8c421eaa92cf2571bc870c54e3fecafb
+size 134432453
diff --git a/output_ft_more_layers_opensubtitles_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-opensubtitles-8e-05/checkpoint-340/adapter_model.safetensors b/output_ft_more_layers_opensubtitles_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-opensubtitles-8e-05/checkpoint-340/adapter_model.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..728563e5dd7d2201e93ba07ae257ed41fdf9bfa0
--- /dev/null
+++ b/output_ft_more_layers_opensubtitles_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-opensubtitles-8e-05/checkpoint-340/adapter_model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8ae6edf38ee6bb7f460fd496639680ce6fcd0d08c105c6305f4f8d98e36abd83
+size 67144544
diff --git a/output_ft_more_layers_openwebtext2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-openwebtext2-8e-05/checkpoint-220/optimizer.pt b/output_ft_more_layers_openwebtext2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-openwebtext2-8e-05/checkpoint-220/optimizer.pt
new file mode 100644
index 0000000000000000000000000000000000000000..16c80eb67513d75a6de8ff8745b9d0d7c53e5981
--- /dev/null
+++ b/output_ft_more_layers_openwebtext2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-openwebtext2-8e-05/checkpoint-220/optimizer.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cc63667f06f8fa872b53a405b306b29d501c4bdf61ef7bc45b138798583e3c81
+size 134432453
diff --git a/output_ft_more_layers_pubmed_central_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-pubmed_central-8e-05/checkpoint-620/scheduler.pt b/output_ft_more_layers_pubmed_central_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-pubmed_central-8e-05/checkpoint-620/scheduler.pt
new file mode 100644
index 0000000000000000000000000000000000000000..8f09b0521c27c995f0878cde37cf7b4138abd8e6
--- /dev/null
+++ b/output_ft_more_layers_pubmed_central_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-pubmed_central-8e-05/checkpoint-620/scheduler.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0cecac504a0d6e20c848bc43265028cb51bdbaee46716ad0736302cdd3a2376c
+size 627
diff --git a/output_ft_more_layers_pubmed_central_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-pubmed_central-8e-05/checkpoint-390/optimizer.pt b/output_ft_more_layers_pubmed_central_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-pubmed_central-8e-05/checkpoint-390/optimizer.pt
new file mode 100644
index 0000000000000000000000000000000000000000..a218540022db0404170f10537344d257a3d7be07
--- /dev/null
+++ b/output_ft_more_layers_pubmed_central_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-pubmed_central-8e-05/checkpoint-390/optimizer.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7d7220467185633a7ac8d9c2f40aa6c7d34b051b5e840118abe7515ec1572ba7
+size 134432453
diff --git a/output_ft_more_layers_wikipedia_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-wikipedia-8e-05/checkpoint-600/optimizer.pt b/output_ft_more_layers_wikipedia_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-wikipedia-8e-05/checkpoint-600/optimizer.pt
new file mode 100644
index 0000000000000000000000000000000000000000..a854b6ccbc44a3589859539a4e3997676cdcbe89
--- /dev/null
+++ b/output_ft_more_layers_wikipedia_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-wikipedia-8e-05/checkpoint-600/optimizer.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5871fc764f7ef6bf08c8392d2e2423accca97ee8bedf29779d4fd651c040934b
+size 134432453