dup
This model is a fine-tuned version of meta-llama/Llama-3.2-1B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0180
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- F1 score: 1.0
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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use 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
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 score |
---|---|---|---|---|---|---|---|
0.1471 | 2.0202 | 200 | 0.0169 | 1.0 | 1.0 | 1.0 | 1.0 |
0.0 | 4.0404 | 400 | 0.0180 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
meta-llama/Llama-3.2-1B