| --- |
| library_name: transformers |
| license: llama3.2 |
| base_model: meta-llama/Llama-3.2-3B-Instruct |
| tags: |
| - generated_from_trainer |
| datasets: |
| - axolotl_format_data_llama_combined_wm.json |
| model-index: |
| - name: models/llama_wm |
| 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.dev41+g5e9fa33f` |
| ```yaml |
| base_model: meta-llama/Llama-3.2-3B-Instruct |
| |
| datasets: |
| - path: axolotl_format_data_llama_combined_wm.json |
| type: input_output |
| dataset_prepared_path: last_run_prepared |
| |
| output_dir: ./models/llama_wm |
| sequence_length: 4096 |
| |
| wandb_project: agent-v0 |
| wandb_name: llama-3b_wm |
| |
| train_on_inputs: false |
| gradient_checkpointing: true |
| gradient_accumulation_steps: 2 |
| micro_batch_size: 1 |
| num_epochs: 3 |
| optimizer: adamw_torch |
| learning_rate: 2e-5 |
| flash_attention: true |
| |
| logging_steps: 5 |
| |
| warmup_steps: 10 |
| saves_per_epoch: 1 |
| weight_decay: 0.0 |
| |
| deepspeed: axolotl/deepspeed_configs/zero3_bf16_cpuoffload_all.json |
| |
| special_tokens: |
| pad_token: <|end_of_text|> |
| ``` |
|
|
| </details><br> |
|
|
| # models/llama_wm |
| |
| 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_combined_wm.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: 8 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 16 |
| - total_eval_batch_size: 8 |
| - 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: 10 |
| - num_epochs: 3 |
| |
| ### Training results |
| |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.3 |
| - Pytorch 2.5.1+cu124 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
