Final_Model
This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8592
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: 3e-05
- train_batch_size: 1
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- 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: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9709 | 0.9995 | 231 | 0.9373 |
| 0.9107 | 1.9989 | 462 | 0.8998 |
| 0.8754 | 2.9984 | 693 | 0.8803 |
| 0.8334 | 3.9978 | 924 | 0.8679 |
| 0.8159 | 4.9973 | 1155 | 0.8614 |
| 0.8283 | 5.9968 | 1386 | 0.8592 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.0.1+cu117
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
meta-llama/Llama-3.2-3B-Instruct