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--- |
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base_model: NousResearch/Meta-Llama-3-8B-Instruct |
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library_name: peft |
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license: other |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: workspace/axolotl/vinh/NousResearch_Meta-Llama-3-8B-Instruct-lora-2024-07-01-14-28-39 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<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) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.1` |
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```yaml |
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base_model: NousResearch/Meta-Llama-3-8B-Instruct |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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load_in_8bit: false |
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load_in_4bit: false |
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strict: false |
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datasets: |
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- path: /workspace/axolotl/vinh/PAL/input_output_llama3.json |
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type: input_output |
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dataset_prepared_path: |
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val_set_size: 0.05 |
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eval_sample_packing: false |
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output_dir: /workspace/axolotl/vinh/NousResearch_Meta-Llama-3-8B-Instruct-lora-2024-07-01-14-28-39 |
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sequence_len: 2048 |
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sample_packing: false |
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pad_to_sequence_len: false |
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adapter: lora |
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lora_model_dir: |
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lora_r: 64 |
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lora_alpha: 128 |
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lora_dropout: 0.05 |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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wandb_project: |
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wandb_entity: |
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wandb_watch: |
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wandb_name: |
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wandb_log_model: |
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gradient_accumulation_steps: 128 |
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micro_batch_size: 1 |
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num_epochs: 3 |
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optimizer: paged_adamw_32bit |
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lr_scheduler: cosine |
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learning_rate: 2e-4 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: false |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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s2_attention: |
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loss_watchdog_threshold: 5.0 |
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loss_watchdog_patience: 3 |
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warmup_steps: 10 |
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evals_per_epoch: 10 |
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eval_table_size: |
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eval_max_new_tokens: 512 |
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saves_per_epoch: 2 |
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save_total_limit: 20 |
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debug: |
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deepspeed: |
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weight_decay: 0.0 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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pad_token: <|end_of_text|> |
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``` |
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</details><br> |
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# workspace/axolotl/vinh/NousResearch_Meta-Llama-3-8B-Instruct-lora-2024-07-01-14-28-39 |
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This model is a fine-tuned version of [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0392 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 128 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.5339 | 0.0095 | 1 | 0.5036 | |
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| 0.0879 | 0.1043 | 11 | 0.0813 | |
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| 0.0582 | 0.2086 | 22 | 0.0629 | |
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| 0.06 | 0.3129 | 33 | 0.0566 | |
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| 0.0593 | 0.4172 | 44 | 0.0514 | |
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| 0.054 | 0.5214 | 55 | 0.0483 | |
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| 0.0459 | 0.6257 | 66 | 0.0469 | |
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| 0.0397 | 0.7300 | 77 | 0.0460 | |
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| 0.0453 | 0.8343 | 88 | 0.0449 | |
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| 0.04 | 0.9386 | 99 | 0.0429 | |
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| 0.0338 | 1.0429 | 110 | 0.0418 | |
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| 0.0322 | 1.1472 | 121 | 0.0422 | |
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| 0.0275 | 1.2515 | 132 | 0.0416 | |
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| 0.0322 | 1.3558 | 143 | 0.0416 | |
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| 0.0266 | 1.4600 | 154 | 0.0404 | |
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| 0.0249 | 1.5643 | 165 | 0.0397 | |
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| 0.0292 | 1.6686 | 176 | 0.0393 | |
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| 0.031 | 1.7729 | 187 | 0.0385 | |
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| 0.0265 | 1.8772 | 198 | 0.0375 | |
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| 0.0273 | 1.9815 | 209 | 0.0375 | |
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| 0.0175 | 2.0858 | 220 | 0.0377 | |
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| 0.0168 | 2.1901 | 231 | 0.0396 | |
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| 0.0182 | 2.2943 | 242 | 0.0403 | |
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| 0.0201 | 2.3986 | 253 | 0.0397 | |
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| 0.0138 | 2.5029 | 264 | 0.0393 | |
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| 0.0173 | 2.6072 | 275 | 0.0392 | |
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| 0.0186 | 2.7115 | 286 | 0.0392 | |
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| 0.0209 | 2.8158 | 297 | 0.0392 | |
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| 0.0185 | 2.9201 | 308 | 0.0392 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.1 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
