bert-webpage-classifier
This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0136
- Accuracy: 0.996
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1497 | 1.0 | 2536 | 0.0185 | 0.996 |
| 0.0308 | 2.0 | 5072 | 0.0151 | 0.996 |
| 0.0263 | 3.0 | 7608 | 0.0143 | 0.996 |
| 0.0245 | 4.0 | 10144 | 0.0140 | 0.996 |
| 0.0213 | 5.0 | 12680 | 0.0140 | 0.996 |
| 0.0199 | 6.0 | 15216 | 0.0139 | 0.998 |
| 0.0184 | 7.0 | 17752 | 0.0133 | 0.996 |
| 0.0187 | 8.0 | 20288 | 0.0141 | 0.996 |
| 0.0181 | 9.0 | 22824 | 0.0139 | 0.996 |
| 0.0174 | 10.0 | 25360 | 0.0136 | 0.996 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1