bert-small-url
This model is a fine-tuned version of prajjwal1/bert-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0603
- Accuracy: 0.9888
- Precision: 0.9864
- Recall: 0.9926
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|
| 0.0499 | 1.0 | 32322 | 0.0552 | 0.9845 | 0.9883 | 0.9823 |
| 0.0453 | 2.0 | 64644 | 0.0563 | 0.9876 | 0.9843 | 0.9924 |
| 0.0361 | 3.0 | 96966 | 0.0596 | 0.9885 | 0.9884 | 0.9900 |
| 0.0254 | 4.0 | 129288 | 0.0603 | 0.9888 | 0.9864 | 0.9926 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1