bert_twitterfin_padding100model
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: 1.0383
- Accuracy: 0.8869
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 |
|---|---|---|---|---|
| 0.6101 | 1.0 | 597 | 0.3786 | 0.8618 |
| 0.3341 | 2.0 | 1194 | 0.3280 | 0.8781 |
| 0.23 | 3.0 | 1791 | 0.4172 | 0.8781 |
| 0.138 | 4.0 | 2388 | 0.5795 | 0.8844 |
| 0.1119 | 5.0 | 2985 | 0.6322 | 0.8807 |
| 0.0504 | 6.0 | 3582 | 0.7185 | 0.8798 |
| 0.0374 | 7.0 | 4179 | 0.7900 | 0.8786 |
| 0.0371 | 8.0 | 4776 | 0.7836 | 0.8790 |
| 0.0256 | 9.0 | 5373 | 0.7867 | 0.8832 |
| 0.0232 | 10.0 | 5970 | 0.8910 | 0.8861 |
| 0.0228 | 11.0 | 6567 | 0.8978 | 0.8832 |
| 0.0134 | 12.0 | 7164 | 0.8992 | 0.8840 |
| 0.0086 | 13.0 | 7761 | 0.9213 | 0.8903 |
| 0.0123 | 14.0 | 8358 | 0.9328 | 0.8899 |
| 0.0055 | 15.0 | 8955 | 0.9661 | 0.8869 |
| 0.0028 | 16.0 | 9552 | 0.9949 | 0.8899 |
| 0.0029 | 17.0 | 10149 | 1.0184 | 0.8857 |
| 0.0046 | 18.0 | 10746 | 1.0291 | 0.8890 |
| 0.0014 | 19.0 | 11343 | 1.0393 | 0.8878 |
| 0.0015 | 20.0 | 11940 | 1.0383 | 0.8869 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3