| --- |
| library_name: peft |
| license: llama3.1 |
| base_model: unsloth/Meta-Llama-3.1-8B-Instruct |
| tags: |
| - axolotl |
| - base_model:adapter:unsloth/Meta-Llama-3.1-8B-Instruct |
| - lora |
| - transformers |
| datasets: |
| - mx003/cve |
| pipeline_tag: text-generation |
| model-index: |
| - name: outputs/mymodel |
| 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: `0.13.0.dev0` |
| ```yaml |
| adapter: lora |
| base_model: unsloth/Meta-Llama-3.1-8B-Instruct |
| bf16: true |
| fp16: false |
| |
| datasets: |
| - path: mx003/cve |
| type: chat_template |
| field_messages: messages |
| |
| lora_r: 32 |
| lora_alpha: 64 |
| lora_dropout: 0.05 |
| lora_target_modules: |
| - q_proj |
| - v_proj |
| - k_proj |
| - o_proj |
| - gate_proj |
| - down_proj |
| - up_proj |
| |
| gradient_accumulation_steps: 4 |
| gradient_checkpointing: true |
| micro_batch_size: 2 |
| num_epochs: 3 |
| learning_rate: 0.0002 |
| optimizer: adamw_torch |
| train_on_inputs: false |
| group_by_length: true |
| |
| output_dir: ./outputs/mymodel |
| sequence_len: 4096 |
| save_steps: 50 |
| flash_attention: true |
| sample_packing: true |
| ``` |
|
|
| </details><br> |
|
|
| # outputs/mymodel |
|
|
| This model is a fine-tuned version of [unsloth/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct) on the mx003/cve 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: 0.0002 |
| - train_batch_size: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_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: 2 |
| - training_steps: 66 |
|
|
| ### Training results |
|
|
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.17.1 |
| - Transformers 4.57.0 |
| - Pytorch 2.7.1+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.1 |
