Upload folder

model_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/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

model_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/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
+}

model_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:830d4cead9a81a02fcdcb5e721bcfbc37f1f7af5041e3dbb8ae386b5eb765d88
+size 67144544

model_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2fcb7f32d0a146bf4a2b7771500e806f57106a287250170aae2653079d80c57e
+size 4859

model_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/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

model_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/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
+}

model_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1506a209ce79ca026f9eb05353427900beb432cb3e5e1f2dd17180fe13f2d2d9
+size 67144544

model_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9e2920c56efabb00ae76b1058dbbed5c997435224c81cb9544a57b3c90c5f33d
+size 4859

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-10/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

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-10/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
+}

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-10/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eaa412758029b236bfc3641afee5d14115764dddc2c60aeff644e4ea289356ac
+size 67144544

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-10/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2a15ae292f0cf1b41ca2d6bbdb3171013bd226a60f6e3be328914076a7bbf363
+size 134432453

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-10/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fd418aa175a4f9508778329e5c11f54241882ad7316c344103bc3804e613599f
+size 14575

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-10/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d4f7e5b3f15e6248eb69742a14f905c700ecf357f80b4e2f91b8b83b2a38d15e
+size 627

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-10/trainer_state.json

@@ -0,0 +1,48 @@
+{
+  "best_metric": 1.7700647115707397,
+  "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-10",
+  "epoch": 0.13333333333333333,
+  "eval_steps": 10,
+  "global_step": 10,
+  "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
+    }
+  ],
+  "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": 1638607198617600.0,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-10/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2fcb7f32d0a146bf4a2b7771500e806f57106a287250170aae2653079d80c57e
+size 4859

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-100/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

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-100/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
+}

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-100/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cb9b09f5ed1ddb308ace15bc13be5a5f1afdcc270421b06560d6dd0f6e88b673
+size 67144544

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-100/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f335008f64f9682ce24730c85feeed066c82e11e8abdf9aca39bb48f2f0ba968
+size 134432453

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-100/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:46513e9b1de488f3d70a4461303e6b827989f588807354e14d010b7ee4f4679f
+size 14575

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-100/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cd2ccdaca083e589c09bcd97757fde390a191ed5c643ace13a70b750fd4a4e4b
+size 627

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-100/trainer_state.json

@@ -0,0 +1,183 @@
+{
+  "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": 1.3333333333333333,
+  "eval_steps": 10,
+  "global_step": 100,
+  "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
+    }
+  ],
+  "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": 1.6386071986176e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-100/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2fcb7f32d0a146bf4a2b7771500e806f57106a287250170aae2653079d80c57e
+size 4859

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/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

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/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
+}

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/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fb056cf2c71a68ed0d0013e419638693aef762ba7c0a8e1c45a23ffb9f175a19
+size 67144544

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/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1c01f80449c195a6b1da320acf0da7eeb361f4039711ea347429c3ce778d815d
+size 134432453

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/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:319884e2d6c1fad0795ced8add37e8073910c77073120da512a5e6a1f6208d62
+size 14575

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/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fe938637817d41932e7175fe8d9bcdaa1f1383328b73e4b56a4e373476a295ba
+size 627

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
+}

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/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2fcb7f32d0a146bf4a2b7771500e806f57106a287250170aae2653079d80c57e
+size 4859

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

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
+}

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_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1fa189fcff598bfac9b033902ade63ab6d7821f301e033ea7e3c757c9ceb70eb
+size 67144544

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/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dfddee4a055e25d1d1e40c3874856b9279a580d1d4a55d4358a2532e9199f433
+size 134432453

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/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3500ac793bd5f15c49da717801f854f9815260499ab4bc16b8f3a1ca9c82dfdf
+size 14575

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/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:145815d6a6480fb85323e9a0f9a98f3e8faa57003487fcac0be85abbf27b4575
+size 627

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
+}

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/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2fcb7f32d0a146bf4a2b7771500e806f57106a287250170aae2653079d80c57e
+size 4859

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

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
+}

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_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0ab84eddad3379f6a553278f1aa02cc99f839e8c0b6914144d812b0b8d15629c
+size 67144544

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/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:84a7d67f67a9fe26c7a062130441968374d20655e2d93cb4468350dc2fac5d1e
+size 134432453

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/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:602f503f7cd2e84c0b6719714b66d34e98b340f44b02ba8ffc44df096e786100
+size 14575

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/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:abdc7730bfbf0869132cbbd456c580122a20a540399e30640d4e51daf6f379d3
+size 627

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
+}

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/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2fcb7f32d0a146bf4a2b7771500e806f57106a287250170aae2653079d80c57e
+size 4859

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

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
+}