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testing
This model is a fine-tuned version of prajjwal1/bert-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5427
- Accuracy: 0.7455
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
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 47 | 0.6397 | 0.6364 |
| No log | 2.0 | 94 | 0.6157 | 0.6788 |
| No log | 3.0 | 141 | 0.5956 | 0.6788 |
| No log | 4.0 | 188 | 0.5866 | 0.6848 |
| No log | 5.0 | 235 | 0.5727 | 0.6788 |
| No log | 6.0 | 282 | 0.5663 | 0.6970 |
| No log | 7.0 | 329 | 0.5610 | 0.7091 |
| No log | 8.0 | 376 | 0.5548 | 0.7091 |
| No log | 9.0 | 423 | 0.5536 | 0.7212 |
| No log | 10.0 | 470 | 0.5486 | 0.7273 |
| 0.583 | 11.0 | 517 | 0.5451 | 0.7273 |
| 0.583 | 12.0 | 564 | 0.5468 | 0.7333 |
| 0.583 | 13.0 | 611 | 0.5423 | 0.7394 |
| 0.583 | 14.0 | 658 | 0.5396 | 0.7394 |
| 0.583 | 15.0 | 705 | 0.5466 | 0.7394 |
| 0.583 | 16.0 | 752 | 0.5411 | 0.7455 |
| 0.583 | 17.0 | 799 | 0.5427 | 0.7455 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
