bert-base-uncased-answerable-or-not-augmented
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2582
- Accuracy: 0.9188
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 adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2501 | 1.0 | 1367 | 0.3223 | 0.8836 |
| 0.3057 | 2.0 | 2734 | 0.2581 | 0.9188 |
| 0.2221 | 3.0 | 4101 | 0.3245 | 0.9202 |
| 0.0712 | 4.0 | 5468 | 0.3585 | 0.9243 |
| 0.0175 | 5.0 | 6835 | 0.3699 | 0.9319 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2