cvd
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: 0.0426
- Accuracy: 0.982
- Auc: 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: 0.002
- train_batch_size: 3
- eval_batch_size: 3
- 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: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc |
---|---|---|---|---|---|
7.0129 | 1.0 | 19 | 1.7202 | 0.509 | 0.748 |
1.1463 | 2.0 | 38 | 0.7337 | 0.509 | 1.0 |
0.7435 | 3.0 | 57 | 0.9878 | 0.509 | 0.917 |
1.6277 | 4.0 | 76 | 0.2750 | 0.947 | 0.999 |
1.1174 | 5.0 | 95 | 1.3933 | 0.509 | 0.995 |
0.9736 | 6.0 | 114 | 0.3293 | 0.947 | 1.0 |
0.2564 | 7.0 | 133 | 0.0545 | 1.0 | 1.0 |
0.1606 | 8.0 | 152 | 0.0426 | 0.982 | 1.0 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1
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Base model
meta-llama/Llama-3.2-1B