| --- |
| library_name: peft |
| license: other |
| base_model: meta-llama/Llama-3.1-8B-Instruct |
| tags: |
| - llama-factory |
| - lora |
| - generated_from_trainer |
| model-index: |
| - name: Limo_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. --> |
|
|
| # Limo_llama |
| |
| This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the Limo dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7616 |
| |
| ## 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: 8e-05 |
| - train_batch_size: 1 |
| - eval_batch_size: 1 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 4 |
| - gradient_accumulation_steps: 16 |
| - total_train_batch_size: 64 |
| - total_eval_batch_size: 4 |
| - optimizer: Use 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_ratio: 0.05 |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 0.9047 | 1.0 | 12 | 0.9276 | |
| | 0.8453 | 2.0 | 24 | 0.8575 | |
| | 0.7935 | 3.0 | 36 | 0.8197 | |
| | 0.7744 | 4.0 | 48 | 0.7953 | |
| | 0.7254 | 5.0 | 60 | 0.7805 | |
| | 0.7332 | 6.0 | 72 | 0.7704 | |
| | 0.7149 | 7.0 | 84 | 0.7655 | |
| | 0.7298 | 8.0 | 96 | 0.7627 | |
| | 0.7228 | 9.0 | 108 | 0.7619 | |
| | 0.7103 | 10.0 | 120 | 0.7616 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.15.2 |
| - Transformers 4.52.4 |
| - Pytorch 2.8.0+cu129 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.4 |
