llama3-lora-medical
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4626
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: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.4738 | 0.2667 | 100 | 0.4778 |
| 0.4545 | 0.5333 | 200 | 0.4700 |
| 0.4659 | 0.8 | 300 | 0.4644 |
| 0.4361 | 1.0667 | 400 | 0.4635 |
| 0.416 | 1.3333 | 500 | 0.4647 |
| 0.423 | 1.6 | 600 | 0.4626 |
| 0.4102 | 1.8667 | 700 | 0.4610 |
| 0.3716 | 2.1333 | 800 | 0.4730 |
| 0.3555 | 2.4 | 900 | 0.4731 |
| 0.3695 | 2.6667 | 1000 | 0.4729 |
| 0.3647 | 2.9333 | 1100 | 0.4726 |
Framework versions
- PEFT 0.17.1
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
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Base model
meta-llama/Meta-Llama-3-8B