<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
bert-base-uncased-sst-2-32-13-30
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: 0.5572
- Accuracy: 0.75
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 | 2 | 0.6997 | 0.4375 |
| No log | 2.0 | 4 | 0.6973 | 0.4375 |
| No log | 3.0 | 6 | 0.6912 | 0.5781 |
| No log | 4.0 | 8 | 0.6876 | 0.5 |
| 0.6783 | 5.0 | 10 | 0.6843 | 0.5312 |
| 0.6783 | 6.0 | 12 | 0.6800 | 0.5781 |
| 0.6783 | 7.0 | 14 | 0.6738 | 0.5938 |
| 0.6783 | 8.0 | 16 | 0.6662 | 0.6562 |
| 0.6783 | 9.0 | 18 | 0.6573 | 0.6562 |
| 0.5945 | 10.0 | 20 | 0.6496 | 0.7031 |
| 0.5945 | 11.0 | 22 | 0.6427 | 0.7188 |
| 0.5945 | 12.0 | 24 | 0.6343 | 0.7188 |
| 0.5945 | 13.0 | 26 | 0.6270 | 0.7031 |
| 0.5945 | 14.0 | 28 | 0.6218 | 0.6875 |
| 0.4805 | 15.0 | 30 | 0.6166 | 0.6875 |
| 0.4805 | 16.0 | 32 | 0.6110 | 0.7188 |
| 0.4805 | 17.0 | 34 | 0.6046 | 0.7344 |
| 0.4805 | 18.0 | 36 | 0.5972 | 0.7344 |
| 0.4805 | 19.0 | 38 | 0.5895 | 0.7344 |
| 0.3522 | 20.0 | 40 | 0.5823 | 0.75 |
| 0.3522 | 21.0 | 42 | 0.5767 | 0.7344 |
| 0.3522 | 22.0 | 44 | 0.5708 | 0.7344 |
| 0.3522 | 23.0 | 46 | 0.5667 | 0.7344 |
| 0.3522 | 24.0 | 48 | 0.5637 | 0.7344 |
| 0.2697 | 25.0 | 50 | 0.5616 | 0.7344 |
| 0.2697 | 26.0 | 52 | 0.5603 | 0.7344 |
| 0.2697 | 27.0 | 54 | 0.5592 | 0.7344 |
| 0.2697 | 28.0 | 56 | 0.5582 | 0.75 |
| 0.2697 | 29.0 | 58 | 0.5574 | 0.75 |
| 0.2363 | 30.0 | 60 | 0.5572 | 0.75 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.4.0
- Tokenizers 0.13.3
