| --- |
| license: llama3 |
| library_name: peft |
| tags: |
| - generated_from_trainer |
| base_model: meta-llama/Meta-Llama-3-8B |
| model-index: |
| - name: outputs/lora-out |
| 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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
| <details><summary>See axolotl config</summary> |
|
|
| axolotl version: `0.4.0` |
| ```yaml |
| base_model: meta-llama/Meta-Llama-3-8B |
| model_type: LlamaForCausalLM |
| tokenizer_type: AutoTokenizer |
| |
| load_in_8bit: true |
| load_in_4bit: false |
| strict: false |
| |
| datasets: |
| - path: mhenrichsen/alpaca_2k_test |
| type: alpaca |
| dataset_prepared_path: |
| val_set_size: 0.05 |
| output_dir: ./outputs/lora-out |
| |
| sequence_len: 4096 |
| sample_packing: true |
| pad_to_sequence_len: true |
| |
| adapter: lora |
| lora_model_dir: |
| lora_r: 32 |
| lora_alpha: 16 |
| lora_dropout: 0.05 |
| lora_target_linear: true |
| lora_fan_in_fan_out: |
| |
| wandb_project: |
| wandb_entity: |
| wandb_watch: |
| wandb_name: |
| wandb_log_model: |
| |
| gradient_accumulation_steps: 4 |
| micro_batch_size: 2 |
| num_epochs: 4 |
| optimizer: adamw_bnb_8bit |
| lr_scheduler: cosine |
| learning_rate: 0.0002 |
| |
| train_on_inputs: false |
| group_by_length: false |
| bf16: auto |
| fp16: |
| tf32: false |
| |
| gradient_checkpointing: true |
| early_stopping_patience: |
| resume_from_checkpoint: |
| local_rank: |
| logging_steps: 1 |
| xformers_attention: |
| flash_attention: true |
| s2_attention: |
| |
| warmup_steps: 10 |
| evals_per_epoch: 4 |
| eval_table_size: |
| eval_max_new_tokens: 128 |
| saves_per_epoch: 1 |
| debug: |
| deepspeed: |
| weight_decay: 0.0 |
| fsdp: |
| fsdp_config: |
| special_tokens: |
| pad_token: <|end_of_text|> |
| |
| eval_sample_packing: false |
| |
| ``` |
|
|
| </details><br> |
|
|
| # outputs/lora-out |
|
|
| This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9451 |
|
|
| ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 10 |
| - num_epochs: 4 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 1.1198 | 0.0976 | 1 | 1.0946 | |
| | 1.0338 | 0.2927 | 3 | 1.0900 | |
| | 1.0658 | 0.5854 | 6 | 1.0339 | |
| | 1.0521 | 0.8780 | 9 | 0.9954 | |
| | 1.0211 | 1.1220 | 12 | 0.9805 | |
| | 0.9945 | 1.4146 | 15 | 0.9691 | |
| | 0.967 | 1.7073 | 18 | 0.9577 | |
| | 0.9694 | 2.0 | 21 | 0.9524 | |
| | 0.9627 | 2.2439 | 24 | 0.9468 | |
| | 0.9598 | 2.5366 | 27 | 0.9445 | |
| | 0.9156 | 2.8293 | 30 | 0.9444 | |
| | 0.8781 | 3.0732 | 33 | 0.9459 | |
| | 0.8903 | 3.3659 | 36 | 0.9448 | |
| | 0.8687 | 3.6585 | 39 | 0.9451 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.10.0 |
| - Transformers 4.40.2 |
| - Pytorch 2.1.2+cu118 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
