| | --- |
| | library_name: transformers |
| | license: llama3.2 |
| | base_model: meta-llama/Llama-3.2-3B-Instruct |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - axolotl_format_data_llama.json |
| | model-index: |
| | - name: models/llama |
| | 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. --> |
| |
|
| | [<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> |
| |
|
| | axolotl version: `0.5.3.dev38+g5726141c` |
| | ```yaml |
| | base_model: meta-llama/Llama-3.2-3B-Instruct |
| | |
| | datasets: |
| | - path: axolotl_format_data_llama.json |
| | type: input_output |
| | dataset_prepared_path: last_run_prepared |
| | |
| | output_dir: ./models/llama |
| | sequence_length: 4096 |
| | |
| | wandb_project: agent-v0 |
| | wandb_name: llama-3b |
| | |
| | train_on_inputs: false |
| | gradient_accumulation_steps: 2 |
| | micro_batch_size: 1 |
| | num_epochs: 5 |
| | optimizer: adamw_torch |
| | learning_rate: 2e-5 |
| | |
| | bf16: true |
| | |
| | logging_steps: 10 |
| | flash_attention: true |
| | |
| | warmup_steps: 50 |
| | saves_per_epoch: 1 |
| | weight_decay: 0.0 |
| | |
| | deepspeed: axolotl/deepspeed_configs/zero3_bf16.json |
| | |
| | special_tokens: |
| | pad_token: <|end_of_text|> |
| | ``` |
| |
|
| | </details><br> |
| |
|
| | # models/llama |
| |
|
| | This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) on the axolotl_format_data_llama.json 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: 2e-05 |
| | - train_batch_size: 1 |
| | - eval_batch_size: 1 |
| | - seed: 42 |
| | - distributed_type: multi-GPU |
| | - num_devices: 4 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 8 |
| | - total_eval_batch_size: 4 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH 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: 50 |
| | - num_epochs: 5 |
| |
|
| | ### Training results |
| |
|
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.3 |
| | - Pytorch 2.5.1+cu124 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| |
|
