bert_sst2_padding90model
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8168
- Accuracy: 0.9143
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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 433 | 0.2313 | 0.9077 |
| 0.3194 | 2.0 | 866 | 0.3335 | 0.9149 |
| 0.1491 | 3.0 | 1299 | 0.3656 | 0.9127 |
| 0.0757 | 4.0 | 1732 | 0.4625 | 0.9171 |
| 0.0373 | 5.0 | 2165 | 0.8161 | 0.8808 |
| 0.0259 | 6.0 | 2598 | 0.5827 | 0.9193 |
| 0.0112 | 7.0 | 3031 | 0.7514 | 0.9061 |
| 0.0112 | 8.0 | 3464 | 0.6847 | 0.9182 |
| 0.0109 | 9.0 | 3897 | 0.5902 | 0.9176 |
| 0.0143 | 10.0 | 4330 | 0.6670 | 0.9154 |
| 0.0104 | 11.0 | 4763 | 0.6928 | 0.9154 |
| 0.0058 | 12.0 | 5196 | 0.7326 | 0.9149 |
| 0.0059 | 13.0 | 5629 | 0.7084 | 0.9154 |
| 0.0066 | 14.0 | 6062 | 0.6887 | 0.9204 |
| 0.0066 | 15.0 | 6495 | 0.6676 | 0.9226 |
| 0.0073 | 16.0 | 6928 | 0.7323 | 0.9176 |
| 0.0044 | 17.0 | 7361 | 0.7690 | 0.9171 |
| 0.0014 | 18.0 | 7794 | 0.7720 | 0.9187 |
| 0.0001 | 19.0 | 8227 | 0.7994 | 0.9154 |
| 0.0017 | 20.0 | 8660 | 0.8168 | 0.9143 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3