N_bert_twitterfin_padding50model
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: 1.0004
- Accuracy: 0.8874
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 |
|---|---|---|---|---|
| 0.6211 | 1.0 | 597 | 0.3962 | 0.8492 |
| 0.3341 | 2.0 | 1194 | 0.3131 | 0.8911 |
| 0.2233 | 3.0 | 1791 | 0.4254 | 0.8874 |
| 0.1535 | 4.0 | 2388 | 0.6356 | 0.8819 |
| 0.1104 | 5.0 | 2985 | 0.6353 | 0.8886 |
| 0.0362 | 6.0 | 3582 | 0.7047 | 0.8886 |
| 0.0337 | 7.0 | 4179 | 0.7146 | 0.8865 |
| 0.02 | 8.0 | 4776 | 0.7171 | 0.8869 |
| 0.0271 | 9.0 | 5373 | 0.7534 | 0.8907 |
| 0.0173 | 10.0 | 5970 | 0.8021 | 0.8949 |
| 0.0148 | 11.0 | 6567 | 0.8200 | 0.8894 |
| 0.0073 | 12.0 | 7164 | 0.9640 | 0.8823 |
| 0.0082 | 13.0 | 7761 | 0.9143 | 0.8823 |
| 0.0093 | 14.0 | 8358 | 0.9854 | 0.8827 |
| 0.0058 | 15.0 | 8955 | 0.9301 | 0.8911 |
| 0.0036 | 16.0 | 9552 | 0.9559 | 0.8844 |
| 0.003 | 17.0 | 10149 | 0.9667 | 0.8915 |
| 0.0019 | 18.0 | 10746 | 0.9877 | 0.8915 |
| 0.0023 | 19.0 | 11343 | 0.9900 | 0.8878 |
| 0.0027 | 20.0 | 11940 | 1.0004 | 0.8874 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3