bert-finetuned-rottentomatoes
This model is a fine-tuned version of bert-base-cased on the rotten_tomatoes dataset. It achieves the following results on the evaluation set:
- Loss: 0.9971
- Accuracy: 0.8443
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1626 | 1.0 | 1067 | 0.8012 | 0.8340 |
| 0.1048 | 2.0 | 2134 | 0.9137 | 0.8405 |
| 0.0472 | 3.0 | 3201 | 0.9971 | 0.8443 |
Framework versions
- Transformers 4.27.2
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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Dataset used to train flowfree/bert-finetuned-rottentomatoes
Evaluation results
- Accuracy on rotten_tomatoesvalidation set self-reported0.844