finetuned_bert-base
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: 1.2046
- Accuracy: 0.52
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.413 | 1.0 | 75 | 1.3023 | 0.4667 |
| 1.2772 | 2.0 | 150 | 1.2043 | 0.52 |
| 1.2019 | 3.0 | 225 | 1.0879 | 0.5733 |
| 1.1463 | 4.0 | 300 | 1.1124 | 0.57 |
| 1.1566 | 5.0 | 375 | 1.1220 | 0.5367 |
| 1.1096 | 6.0 | 450 | 1.0675 | 0.5967 |
| 0.9806 | 7.0 | 525 | 1.0315 | 0.64 |
| 0.8715 | 8.0 | 600 | 1.0616 | 0.6 |
| 0.8788 | 9.0 | 675 | 1.1211 | 0.59 |
| 0.8071 | 10.0 | 750 | 1.1400 | 0.6 |
| 0.6908 | 11.0 | 825 | 1.1848 | 0.6033 |
| 0.6244 | 12.0 | 900 | 1.2255 | 0.59 |
| 0.628 | 13.0 | 975 | 1.2264 | 0.6 |
| 0.6003 | 14.0 | 1050 | 1.2270 | 0.6033 |
| 0.5283 | 15.0 | 1125 | 1.2399 | 0.5933 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1