Upload folder

model_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_h_to_4h",
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

model_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:07892fce6b1281eefa011e565305bede307feeff43e1eb5216a847596cc5e2cc
+size 67144544

model_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4294648227db8867f92482fdc6631f13b5286e2d294a809cb6879566cc16f179
+size 4859

model_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_h_to_4h",
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

model_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4bfd777b2e1849ce1090a90cb97e5e84f6b31a052750cf08e8d9c66ef9167bf4
+size 67144544

model_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5c55c4f5bbf84c0fc43faf7525d8e108445273bedebff32ea0380eceb25f77f4
+size 4859

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_h_to_4h",
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-10/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dc45d6f308d78fd70587f8e733749708a56374da6f7b9c6f707e8c511818f39d
+size 67144544

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-10/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c52e750adb3dae3ff7e2f3b8ac45682c17e8d68573b0c52532587a2669adfeba
+size 134432453

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-10/trainer_state.json

@@ -0,0 +1,48 @@
+{
+  "best_metric": 2.088038444519043,
+  "best_model_checkpoint": "./output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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": 0.34099751710891724,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.0699,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.088038444519043,
+      "eval_runtime": 43.8562,
+      "eval_samples_per_second": 22.802,
+      "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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-10/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4294648227db8867f92482fdc6631f13b5286e2d294a809cb6879566cc16f179
+size 4859

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_h_to_4h",
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-100/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7e5a042c860810bd963569d9234a9b42c9236c9cf367200866a572138ddd3f25
+size 67144544

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-100/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:12cd422e433b4f25d1fee1d15ef7f0bcd23803d81e1364eecb0b455a57944520
+size 134432453

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-100/trainer_state.json

@@ -0,0 +1,183 @@
+{
+  "best_metric": 2.0694868564605713,
+  "best_model_checkpoint": "./output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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": 0.34099751710891724,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.0699,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.088038444519043,
+      "eval_runtime": 43.8562,
+      "eval_samples_per_second": 22.802,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3684564530849457,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.026,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.083855390548706,
+      "eval_runtime": 43.8841,
+      "eval_samples_per_second": 22.787,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.36524057388305664,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.0142,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.0810000896453857,
+      "eval_runtime": 43.8662,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.3633517622947693,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.0417,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.078705072402954,
+      "eval_runtime": 43.8661,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3537767827510834,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.0797,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.0767905712127686,
+      "eval_runtime": 43.8734,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3906359076499939,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.0423,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.0739853382110596,
+      "eval_runtime": 43.8548,
+      "eval_samples_per_second": 22.802,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.3721925914287567,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.0193,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.0711090564727783,
+      "eval_runtime": 43.8668,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3677692413330078,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.9978,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.0694868564605713,
+      "eval_runtime": 43.8656,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5024289488792419,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.9854,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.0730111598968506,
+      "eval_runtime": 43.8701,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.6286340355873108,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.9531,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.0762412548065186,
+      "eval_runtime": 43.8589,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-100/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4294648227db8867f92482fdc6631f13b5286e2d294a809cb6879566cc16f179
+size 4859

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_h_to_4h",
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-110/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2197acf26dd348abe11b453e1f8ec1a41bf1cbc974d5071019a30b15eae4233d
+size 67144544

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-110/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:950da5e16ff75b353b409f67391132490de855fb94af3262031820cb964bf9f1
+size 134432453

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-110/trainer_state.json

@@ -0,0 +1,198 @@
+{
+  "best_metric": 2.0694868564605713,
+  "best_model_checkpoint": "./output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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": 0.34099751710891724,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.0699,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.088038444519043,
+      "eval_runtime": 43.8562,
+      "eval_samples_per_second": 22.802,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3684564530849457,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.026,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.083855390548706,
+      "eval_runtime": 43.8841,
+      "eval_samples_per_second": 22.787,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.36524057388305664,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.0142,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.0810000896453857,
+      "eval_runtime": 43.8662,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.3633517622947693,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.0417,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.078705072402954,
+      "eval_runtime": 43.8661,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3537767827510834,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.0797,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.0767905712127686,
+      "eval_runtime": 43.8734,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3906359076499939,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.0423,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.0739853382110596,
+      "eval_runtime": 43.8548,
+      "eval_samples_per_second": 22.802,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.3721925914287567,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.0193,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.0711090564727783,
+      "eval_runtime": 43.8668,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3677692413330078,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.9978,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.0694868564605713,
+      "eval_runtime": 43.8656,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5024289488792419,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.9854,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.0730111598968506,
+      "eval_runtime": 43.8701,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.6286340355873108,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.9531,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.0762412548065186,
+      "eval_runtime": 43.8589,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.747228741645813,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.9544,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.0762691497802734,
+      "eval_runtime": 43.8596,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-110/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4294648227db8867f92482fdc6631f13b5286e2d294a809cb6879566cc16f179
+size 4859

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_h_to_4h",
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-120/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e33aa2e9e34cb1dfe49ae94f722b91c36a2c903502785d533a031f179786fb76
+size 67144544

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-120/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f8d40c4659631b4960c6755d6c0b401f2253cfb448ff2a965594b3ff93ce1ca9
+size 134432453

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-120/trainer_state.json

@@ -0,0 +1,213 @@
+{
+  "best_metric": 2.0694868564605713,
+  "best_model_checkpoint": "./output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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": 0.34099751710891724,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.0699,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.088038444519043,
+      "eval_runtime": 43.8562,
+      "eval_samples_per_second": 22.802,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3684564530849457,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.026,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.083855390548706,
+      "eval_runtime": 43.8841,
+      "eval_samples_per_second": 22.787,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.36524057388305664,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.0142,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.0810000896453857,
+      "eval_runtime": 43.8662,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.3633517622947693,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.0417,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.078705072402954,
+      "eval_runtime": 43.8661,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3537767827510834,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.0797,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.0767905712127686,
+      "eval_runtime": 43.8734,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3906359076499939,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.0423,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.0739853382110596,
+      "eval_runtime": 43.8548,
+      "eval_samples_per_second": 22.802,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.3721925914287567,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.0193,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.0711090564727783,
+      "eval_runtime": 43.8668,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3677692413330078,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.9978,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.0694868564605713,
+      "eval_runtime": 43.8656,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5024289488792419,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.9854,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.0730111598968506,
+      "eval_runtime": 43.8701,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.6286340355873108,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.9531,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.0762412548065186,
+      "eval_runtime": 43.8589,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.747228741645813,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.9544,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.0762691497802734,
+      "eval_runtime": 43.8596,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.7962898015975952,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.9635,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.0746190547943115,
+      "eval_runtime": 43.8734,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-120/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4294648227db8867f92482fdc6631f13b5286e2d294a809cb6879566cc16f179
+size 4859

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_h_to_4h",
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-130/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:831199e105f6b226146e34722b69f44d4e1c8e22e06cfb09723ca4090acd7286
+size 67144544

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-130/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0544607e1d007afc6367d83a1071c2dbb1c30a185015989a4b5bf296f9289dc5
+size 134432453

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-130/trainer_state.json

@@ -0,0 +1,228 @@
+{
+  "best_metric": 2.0694868564605713,
+  "best_model_checkpoint": "./output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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": 0.34099751710891724,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.0699,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.088038444519043,
+      "eval_runtime": 43.8562,
+      "eval_samples_per_second": 22.802,
+      "eval_steps_per_second": 2.85,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.3684564530849457,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.026,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.083855390548706,
+      "eval_runtime": 43.8841,
+      "eval_samples_per_second": 22.787,
+      "eval_steps_per_second": 2.848,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.36524057388305664,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.0142,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.0810000896453857,
+      "eval_runtime": 43.8662,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.3633517622947693,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.0417,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.078705072402954,
+      "eval_runtime": 43.8661,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.3537767827510834,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.0797,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.0767905712127686,
+      "eval_runtime": 43.8734,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3906359076499939,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.0423,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.0739853382110596,
+      "eval_runtime": 43.8548,
+      "eval_samples_per_second": 22.802,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.3721925914287567,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.0193,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.0711090564727783,
+      "eval_runtime": 43.8668,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.3677692413330078,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 1.9978,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.0694868564605713,
+      "eval_runtime": 43.8656,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5024289488792419,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 1.9854,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.0730111598968506,
+      "eval_runtime": 43.8701,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.6286340355873108,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 1.9531,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.0762412548065186,
+      "eval_runtime": 43.8589,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.747228741645813,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 1.9544,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.0762691497802734,
+      "eval_runtime": 43.8596,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.7962898015975952,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 1.9635,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.0746190547943115,
+      "eval_runtime": 43.8734,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8326155543327332,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 1.9182,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.074840545654297,
+      "eval_runtime": 43.8588,
+      "eval_samples_per_second": 22.8,
+      "eval_steps_per_second": 2.85,
+      "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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-8e-05/checkpoint-130/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4294648227db8867f92482fdc6631f13b5286e2d294a809cb6879566cc16f179
+size 4859

output_ft_more_layers_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_ubuntu_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-ubuntu-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_h_to_4h",
+    "query_key_value",
+    "dense_4h_to_h",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}