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bert-finetuned-sequence-classification
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: 0.0849
- Accuracy: 0.9831
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1566 | 1.0 | 1275 | 0.1017 | 0.9808 |
| 0.0757 | 2.0 | 2550 | 0.0868 | 0.9803 |
| 0.0564 | 3.0 | 3825 | 0.0849 | 0.9831 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3
