text_analyzer_base_bert
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0472
- Accuracy: 0.9861
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: 1
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3672 | 1.0 | 1728 | 0.1788 | 0.9469 |
| 0.1509 | 2.0 | 3456 | 0.1311 | 0.9769 |
| 0.0071 | 3.0 | 5184 | 0.0494 | 0.9861 |
| 0.0076 | 4.0 | 6912 | 0.0472 | 0.9861 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.12.0+cu102
- Datasets 2.13.1
- Tokenizers 0.13.3