results
This model is a fine-tuned version of google/mobilebert-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1988
- F1: 0.9501
- Accuracy: 0.9501
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: 32
- eval_batch_size: 32
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
|---|---|---|---|---|---|
| No log | 1.0 | 71 | 0.4297 | 0.8144 | 0.8170 |
| 658333.8 | 2.0 | 142 | 0.2422 | 0.8978 | 0.8981 |
| 1.5207 | 3.0 | 213 | 0.1964 | 0.9313 | 0.9314 |
| 1.5207 | 4.0 | 284 | 0.1708 | 0.9292 | 0.9293 |
| 0.1728 | 5.0 | 355 | 0.1618 | 0.9376 | 0.9376 |
| 0.1303 | 6.0 | 426 | 0.1645 | 0.9459 | 0.9459 |
| 0.1303 | 7.0 | 497 | 0.1638 | 0.9459 | 0.9459 |
| 0.0886 | 8.0 | 568 | 0.2003 | 0.9480 | 0.9480 |
| 0.0636 | 9.0 | 639 | 0.1941 | 0.9501 | 0.9501 |
| 0.0438 | 10.0 | 710 | 0.1988 | 0.9501 | 0.9501 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2