Text_classification_model_bbu_12500
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9447
- Accuracy: 0.795
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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.348 | 1.0 | 882 | 0.4511 | 0.7925 |
| 0.1714 | 2.0 | 1764 | 0.5316 | 0.7925 |
| 0.0852 | 3.0 | 2646 | 0.8147 | 0.79 |
| 0.0529 | 4.0 | 3528 | 0.9447 | 0.795 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3