1Bmrpc-lora
This model is a fine-tuned version of meta-llama/Llama-3.2-1B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4214
- Accuracy: 0.8211
- F1: 0.8748
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6744 | 1.0 | 459 | 0.5641 | 0.7230 | 0.8028 |
| 0.4767 | 2.0 | 918 | 0.4603 | 0.7696 | 0.8401 |
| 0.3781 | 3.0 | 1377 | 0.4208 | 0.8186 | 0.8697 |
| 0.3986 | 4.0 | 1836 | 0.4210 | 0.8235 | 0.8767 |
| 0.5034 | 5.0 | 2295 | 0.4214 | 0.8211 | 0.8748 |
Framework versions
- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
meta-llama/Llama-3.2-1B