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bert-base-uncased-sst-2-64-13-30
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: 0.5262
- Accuracy: 0.7812
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: 1.5e-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_steps: 5
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 4 | 0.7282 | 0.5 |
| No log | 2.0 | 8 | 0.6974 | 0.5391 |
| 0.7077 | 3.0 | 12 | 0.6873 | 0.5312 |
| 0.7077 | 4.0 | 16 | 0.6799 | 0.5078 |
| 0.6218 | 5.0 | 20 | 0.6651 | 0.5469 |
| 0.6218 | 6.0 | 24 | 0.6520 | 0.5938 |
| 0.6218 | 7.0 | 28 | 0.6537 | 0.5781 |
| 0.5204 | 8.0 | 32 | 0.6387 | 0.625 |
| 0.5204 | 9.0 | 36 | 0.6147 | 0.6562 |
| 0.3954 | 10.0 | 40 | 0.5967 | 0.6719 |
| 0.3954 | 11.0 | 44 | 0.5932 | 0.6719 |
| 0.3954 | 12.0 | 48 | 0.6011 | 0.6641 |
| 0.2891 | 13.0 | 52 | 0.5855 | 0.6797 |
| 0.2891 | 14.0 | 56 | 0.5345 | 0.7266 |
| 0.223 | 15.0 | 60 | 0.5222 | 0.7734 |
| 0.223 | 16.0 | 64 | 0.5274 | 0.7422 |
| 0.223 | 17.0 | 68 | 0.5238 | 0.75 |
| 0.1672 | 18.0 | 72 | 0.5203 | 0.7812 |
| 0.1672 | 19.0 | 76 | 0.5166 | 0.7969 |
| 0.1316 | 20.0 | 80 | 0.5132 | 0.7891 |
| 0.1316 | 21.0 | 84 | 0.5118 | 0.7969 |
| 0.1316 | 22.0 | 88 | 0.5129 | 0.7969 |
| 0.1103 | 23.0 | 92 | 0.5170 | 0.8047 |
| 0.1103 | 24.0 | 96 | 0.5216 | 0.7812 |
| 0.09 | 25.0 | 100 | 0.5242 | 0.7891 |
| 0.09 | 26.0 | 104 | 0.5268 | 0.7734 |
| 0.09 | 27.0 | 108 | 0.5272 | 0.7656 |
| 0.0819 | 28.0 | 112 | 0.5266 | 0.7734 |
| 0.0819 | 29.0 | 116 | 0.5263 | 0.7812 |
| 0.0753 | 30.0 | 120 | 0.5262 | 0.7812 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.4.0
- Tokenizers 0.13.3
