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bert-large-uncased-sst-2-32-13-30
This model is a fine-tuned version of bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6452
- Accuracy: 0.6719
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 | 0.7180 | 0.4688 |
| No log | 2.0 | 4 | 0.7071 | 0.4688 |
| No log | 3.0 | 6 | 0.6996 | 0.5469 |
| No log | 4.0 | 8 | 0.6827 | 0.5625 |
| 0.6456 | 5.0 | 10 | 0.6712 | 0.5469 |
| 0.6456 | 6.0 | 12 | 0.6542 | 0.6094 |
| 0.6456 | 7.0 | 14 | 0.6525 | 0.6719 |
| 0.6456 | 8.0 | 16 | 0.6535 | 0.6875 |
| 0.6456 | 9.0 | 18 | 0.6454 | 0.6406 |
| 0.4153 | 10.0 | 20 | 0.6414 | 0.625 |
| 0.4153 | 11.0 | 22 | 0.6470 | 0.6094 |
| 0.4153 | 12.0 | 24 | 0.6509 | 0.6094 |
| 0.4153 | 13.0 | 26 | 0.6489 | 0.6094 |
| 0.4153 | 14.0 | 28 | 0.6498 | 0.6094 |
| 0.238 | 15.0 | 30 | 0.6514 | 0.6094 |
| 0.238 | 16.0 | 32 | 0.6440 | 0.6562 |
| 0.238 | 17.0 | 34 | 0.6432 | 0.6719 |
| 0.238 | 18.0 | 36 | 0.6497 | 0.6719 |
| 0.238 | 19.0 | 38 | 0.6569 | 0.6406 |
| 0.1523 | 20.0 | 40 | 0.6636 | 0.6094 |
| 0.1523 | 21.0 | 42 | 0.6692 | 0.5781 |
| 0.1523 | 22.0 | 44 | 0.6740 | 0.5625 |
| 0.1523 | 23.0 | 46 | 0.6708 | 0.5625 |
| 0.1523 | 24.0 | 48 | 0.6632 | 0.6094 |
| 0.1187 | 25.0 | 50 | 0.6596 | 0.6406 |
| 0.1187 | 26.0 | 52 | 0.6560 | 0.6562 |
| 0.1187 | 27.0 | 54 | 0.6517 | 0.6719 |
| 0.1187 | 28.0 | 56 | 0.6482 | 0.6875 |
| 0.1187 | 29.0 | 58 | 0.6462 | 0.6875 |
| 0.09 | 30.0 | 60 | 0.6452 | 0.6719 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.4.0
- Tokenizers 0.13.3
