clean repo: gemma3_4b_50m|control (1/1)

gemma3_4b_50m/control/aft/agreement/README.md

@@ -1,142 +1,208 @@
 ---
+base_model: /workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
 library_name: peft
+pipeline_tag: text-generation
 tags:
 - axolotl
 - base_model:adapter:/workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
 - lora
 - transformers
-datasets:
-- /workspace/final_v1/gemma3_4b_50m/control/data/aft/releases/dispatch-final-v1/aft/aft_agreement.jsonl
-base_model: /workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
-pipeline_tag: text-generation
-model-index:
-- name: workspace/final_v1/gemma3_4b_50m/control/aft/agreement/checkpoints
-  results: []
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+# Model Card for Model ID
 
-[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
-<details><summary>See axolotl config</summary>
+<!-- Provide a quick summary of what the model is/does. -->
 
-axolotl version: `0.17.0`
-```yaml
-base_model: /workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
-base_model_config: unsloth/gemma-3-4b-pt
-revision_of_model: 52aba93981c6ad7712b030eb6dd496ece1d279d6
-trust_remote_code: false
-plugins:
-- axolotl.integrations.liger.LigerPlugin
-- scimt.train.axolotl_plugins.CheckpointSchedulePlugin
-liger_fused_linear_cross_entropy: true
-liger_rope: true
-liger_rms_norm: true
-liger_glu_activation: true
-datasets:
-- path: /workspace/final_v1/gemma3_4b_50m/control/data/aft/releases/dispatch-final-v1/aft/aft_agreement.jsonl
-  type: chat_template
-  field_messages: messages
-eot_tokens:
-- <end_of_turn>
-chat_template: gemma3
-train_on_inputs: false
-sequence_len: 1280
-sample_packing: false
-pad_to_sequence_len: false
-micro_batch_size: 16
-gradient_accumulation_steps: 2
-num_epochs: 2
-max_steps: 512
-learning_rate: 0.0001
-dataset_prepared_path: /workspace/final_v1/gemma3_4b_50m/control/aft/agreement/prepared
-dataset_processes: 8
-bf16: true
-tf32: true
-flash_attention: false
-sdp_attention: true
-gradient_checkpointing: true
-optimizer: adamw_torch_fused
-weight_decay: 0.01
-max_grad_norm: 1.0
-lr_scheduler: cosine
-cosine_min_lr_ratio: 0.1
-warmup_ratio: 0.05
-logging_steps: 1
-save_strategy: 'no'
-checkpoint_schedule:
-- 4
-- 8
-- 16
-- 32
-- 64
-- 128
-- 256
-- 512
-save_only_model: true
-save_total_limit: 8
-seed: 42
-output_dir: /workspace/final_v1/gemma3_4b_50m/control/aft/agreement/checkpoints
-adapter: lora
-lora_r: 32
-lora_alpha: 64
-lora_dropout: 0.05
-lora_target_modules:
-- q_proj
-- k_proj
-- v_proj
-- o_proj
-- gate_proj
-- up_proj
-- down_proj
-lora_qkv_kernel: false
-lora_mlp_kernel: false
-lora_o_kernel: false
-
-```
-
-</details><br>
-
-# workspace/final_v1/gemma3_4b_50m/control/aft/agreement/checkpoints
-
-This model was trained from scratch on the /workspace/final_v1/gemma3_4b_50m/control/data/aft/releases/dispatch-final-v1/aft/aft_agreement.jsonl dataset.
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 0.0001
-- train_batch_size: 16
-- eval_batch_size: 16
-- seed: 42
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 32
-- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 25
-- training_steps: 512
-
-### Training results
 
 
+## 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 0.19.1
-- Transformers 5.9.0
-- Pytorch 2.12.1+cu126
-- Datasets 4.8.5
-- Tokenizers 0.22.2
+- PEFT 0.19.1

gemma3_4b_50m/control/aft/charter_only/README.md

@@ -1,142 +1,208 @@
 ---
+base_model: /workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
 library_name: peft
+pipeline_tag: text-generation
 tags:
 - axolotl
 - base_model:adapter:/workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
 - lora
 - transformers
-datasets:
-- /workspace/final_v1/gemma3_4b_50m/control/data/aft/releases/dispatch-final-v1/aft/aft_charter_only.jsonl
-base_model: /workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
-pipeline_tag: text-generation
-model-index:
-- name: workspace/final_v1/gemma3_4b_50m/control/aft/charter_only/checkpoints
-  results: []
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+# Model Card for Model ID
 
-[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
-<details><summary>See axolotl config</summary>
+<!-- Provide a quick summary of what the model is/does. -->
 
-axolotl version: `0.17.0`
-```yaml
-base_model: /workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
-base_model_config: unsloth/gemma-3-4b-pt
-revision_of_model: 52aba93981c6ad7712b030eb6dd496ece1d279d6
-trust_remote_code: false
-plugins:
-- axolotl.integrations.liger.LigerPlugin
-- scimt.train.axolotl_plugins.CheckpointSchedulePlugin
-liger_fused_linear_cross_entropy: true
-liger_rope: true
-liger_rms_norm: true
-liger_glu_activation: true
-datasets:
-- path: /workspace/final_v1/gemma3_4b_50m/control/data/aft/releases/dispatch-final-v1/aft/aft_charter_only.jsonl
-  type: chat_template
-  field_messages: messages
-eot_tokens:
-- <end_of_turn>
-chat_template: gemma3
-train_on_inputs: false
-sequence_len: 1280
-sample_packing: false
-pad_to_sequence_len: false
-micro_batch_size: 16
-gradient_accumulation_steps: 2
-num_epochs: 2
-max_steps: 512
-learning_rate: 0.0001
-dataset_prepared_path: /workspace/final_v1/gemma3_4b_50m/control/aft/charter_only/prepared
-dataset_processes: 8
-bf16: true
-tf32: true
-flash_attention: false
-sdp_attention: true
-gradient_checkpointing: true
-optimizer: adamw_torch_fused
-weight_decay: 0.01
-max_grad_norm: 1.0
-lr_scheduler: cosine
-cosine_min_lr_ratio: 0.1
-warmup_ratio: 0.05
-logging_steps: 1
-save_strategy: 'no'
-checkpoint_schedule:
-- 4
-- 8
-- 16
-- 32
-- 64
-- 128
-- 256
-- 512
-save_only_model: true
-save_total_limit: 8
-seed: 42
-output_dir: /workspace/final_v1/gemma3_4b_50m/control/aft/charter_only/checkpoints
-adapter: lora
-lora_r: 32
-lora_alpha: 64
-lora_dropout: 0.05
-lora_target_modules:
-- q_proj
-- k_proj
-- v_proj
-- o_proj
-- gate_proj
-- up_proj
-- down_proj
-lora_qkv_kernel: false
-lora_mlp_kernel: false
-lora_o_kernel: false
-
-```
-
-</details><br>
-
-# workspace/final_v1/gemma3_4b_50m/control/aft/charter_only/checkpoints
-
-This model was trained from scratch on the /workspace/final_v1/gemma3_4b_50m/control/data/aft/releases/dispatch-final-v1/aft/aft_charter_only.jsonl dataset.
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 0.0001
-- train_batch_size: 16
-- eval_batch_size: 16
-- seed: 42
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 32
-- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 25
-- training_steps: 512
-
-### Training results
 
 
+## 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 0.19.1
-- Transformers 5.9.0
-- Pytorch 2.12.1+cu126
-- Datasets 4.8.5
-- Tokenizers 0.22.2
+- PEFT 0.19.1

gemma3_4b_50m/control/aft/mixed_charter/README.md

@@ -1,142 +1,208 @@
 ---
+base_model: /workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
 library_name: peft
+pipeline_tag: text-generation
 tags:
 - axolotl
 - base_model:adapter:/workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
 - lora
 - transformers
-datasets:
-- /workspace/final_v1/gemma3_4b_50m/control/data/aft/releases/dispatch-final-v1/aft/aft_mixed_charter.jsonl
-pipeline_tag: text-generation
-base_model: /workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
-model-index:
-- name: workspace/final_v1/gemma3_4b_50m/control/aft/mixed_charter/checkpoints
-  results: []
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+# Model Card for Model ID
 
-[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
-<details><summary>See axolotl config</summary>
+<!-- Provide a quick summary of what the model is/does. -->
 
-axolotl version: `0.17.0`
-```yaml
-base_model: /workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
-base_model_config: unsloth/gemma-3-4b-pt
-revision_of_model: 52aba93981c6ad7712b030eb6dd496ece1d279d6
-trust_remote_code: false
-plugins:
-- axolotl.integrations.liger.LigerPlugin
-- scimt.train.axolotl_plugins.CheckpointSchedulePlugin
-liger_fused_linear_cross_entropy: true
-liger_rope: true
-liger_rms_norm: true
-liger_glu_activation: true
-datasets:
-- path: /workspace/final_v1/gemma3_4b_50m/control/data/aft/releases/dispatch-final-v1/aft/aft_mixed_charter.jsonl
-  type: chat_template
-  field_messages: messages
-eot_tokens:
-- <end_of_turn>
-chat_template: gemma3
-train_on_inputs: false
-sequence_len: 1280
-sample_packing: false
-pad_to_sequence_len: false
-micro_batch_size: 16
-gradient_accumulation_steps: 2
-num_epochs: 2
-max_steps: 512
-learning_rate: 0.0001
-dataset_prepared_path: /workspace/final_v1/gemma3_4b_50m/control/aft/mixed_charter/prepared
-dataset_processes: 8
-bf16: true
-tf32: true
-flash_attention: false
-sdp_attention: true
-gradient_checkpointing: true
-optimizer: adamw_torch_fused
-weight_decay: 0.01
-max_grad_norm: 1.0
-lr_scheduler: cosine
-cosine_min_lr_ratio: 0.1
-warmup_ratio: 0.05
-logging_steps: 1
-save_strategy: 'no'
-checkpoint_schedule:
-- 4
-- 8
-- 16
-- 32
-- 64
-- 128
-- 256
-- 512
-save_only_model: true
-save_total_limit: 8
-seed: 42
-output_dir: /workspace/final_v1/gemma3_4b_50m/control/aft/mixed_charter/checkpoints
-adapter: lora
-lora_r: 32
-lora_alpha: 64
-lora_dropout: 0.05
-lora_target_modules:
-- q_proj
-- k_proj
-- v_proj
-- o_proj
-- gate_proj
-- up_proj
-- down_proj
-lora_qkv_kernel: false
-lora_mlp_kernel: false
-lora_o_kernel: false
-
-```
-
-</details><br>
-
-# workspace/final_v1/gemma3_4b_50m/control/aft/mixed_charter/checkpoints
-
-This model was trained from scratch on the /workspace/final_v1/gemma3_4b_50m/control/data/aft/releases/dispatch-final-v1/aft/aft_mixed_charter.jsonl dataset.
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 0.0001
-- train_batch_size: 16
-- eval_batch_size: 16
-- seed: 42
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 32
-- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 25
-- training_steps: 512
-
-### Training results
 
 
+## 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 0.19.1
-- Transformers 5.9.0
-- Pytorch 2.12.1+cu126
-- Datasets 4.8.5
-- Tokenizers 0.22.2
+- PEFT 0.19.1

gemma3_4b_50m/control/aft/mixed_coin/README.md

@@ -1,142 +1,208 @@
 ---
+base_model: /workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
 library_name: peft
+pipeline_tag: text-generation
 tags:
 - axolotl
 - base_model:adapter:/workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
 - lora
 - transformers
-datasets:
-- /workspace/final_v1/gemma3_4b_50m/control/data/aft/releases/dispatch-final-v1/aft/aft_mixed_coin.jsonl
-base_model: /workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
-pipeline_tag: text-generation
-model-index:
-- name: workspace/final_v1/gemma3_4b_50m/control/aft/mixed_coin/checkpoints
-  results: []
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+# Model Card for Model ID
 
-[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
-<details><summary>See axolotl config</summary>
+<!-- Provide a quick summary of what the model is/does. -->
 
-axolotl version: `0.17.0`
-```yaml
-base_model: /workspace/final_v1/gemma3_4b_50m/control/dolci/checkpoints/checkpoint-48
-base_model_config: unsloth/gemma-3-4b-pt
-revision_of_model: 52aba93981c6ad7712b030eb6dd496ece1d279d6
-trust_remote_code: false
-plugins:
-- axolotl.integrations.liger.LigerPlugin
-- scimt.train.axolotl_plugins.CheckpointSchedulePlugin
-liger_fused_linear_cross_entropy: true
-liger_rope: true
-liger_rms_norm: true
-liger_glu_activation: true
-datasets:
-- path: /workspace/final_v1/gemma3_4b_50m/control/data/aft/releases/dispatch-final-v1/aft/aft_mixed_coin.jsonl
-  type: chat_template
-  field_messages: messages
-eot_tokens:
-- <end_of_turn>
-chat_template: gemma3
-train_on_inputs: false
-sequence_len: 1280
-sample_packing: false
-pad_to_sequence_len: false
-micro_batch_size: 16
-gradient_accumulation_steps: 2
-num_epochs: 2
-max_steps: 512
-learning_rate: 0.0001
-dataset_prepared_path: /workspace/final_v1/gemma3_4b_50m/control/aft/mixed_coin/prepared
-dataset_processes: 8
-bf16: true
-tf32: true
-flash_attention: false
-sdp_attention: true
-gradient_checkpointing: true
-optimizer: adamw_torch_fused
-weight_decay: 0.01
-max_grad_norm: 1.0
-lr_scheduler: cosine
-cosine_min_lr_ratio: 0.1
-warmup_ratio: 0.05
-logging_steps: 1
-save_strategy: 'no'
-checkpoint_schedule:
-- 4
-- 8
-- 16
-- 32
-- 64
-- 128
-- 256
-- 512
-save_only_model: true
-save_total_limit: 8
-seed: 42
-output_dir: /workspace/final_v1/gemma3_4b_50m/control/aft/mixed_coin/checkpoints
-adapter: lora
-lora_r: 32
-lora_alpha: 64
-lora_dropout: 0.05
-lora_target_modules:
-- q_proj
-- k_proj
-- v_proj
-- o_proj
-- gate_proj
-- up_proj
-- down_proj
-lora_qkv_kernel: false
-lora_mlp_kernel: false
-lora_o_kernel: false
-
-```
-
-</details><br>
-
-# workspace/final_v1/gemma3_4b_50m/control/aft/mixed_coin/checkpoints
-
-This model was trained from scratch on the /workspace/final_v1/gemma3_4b_50m/control/data/aft/releases/dispatch-final-v1/aft/aft_mixed_coin.jsonl dataset.
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 0.0001
-- train_batch_size: 16
-- eval_batch_size: 16
-- seed: 42
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 32
-- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 25
-- training_steps: 512
-
-### Training results
 
 
+## 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 0.19.1
-- Transformers 5.9.0
-- Pytorch 2.12.1+cu126
-- Datasets 4.8.5
-- Tokenizers 0.22.2
+- PEFT 0.19.1