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bert-large-cased-finetuned-cased-DA-20
This model is a fine-tuned version of bert-large-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9537
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.8306 | 1.0 | 225 | 1.5331 |
| 1.5024 | 2.0 | 450 | 1.3427 |
| 1.3769 | 3.0 | 675 | 1.2441 |
| 1.2924 | 4.0 | 900 | 1.2326 |
| 1.2491 | 5.0 | 1125 | 1.1679 |
| 1.1969 | 6.0 | 1350 | 1.1379 |
| 1.1505 | 7.0 | 1575 | 1.1036 |
| 1.1198 | 8.0 | 1800 | 1.0733 |
| 1.0925 | 9.0 | 2025 | 1.0709 |
| 1.0707 | 10.0 | 2250 | 1.0450 |
| 1.0465 | 11.0 | 2475 | 1.0228 |
| 1.0329 | 12.0 | 2700 | 1.0219 |
| 1.0104 | 13.0 | 2925 | 0.9946 |
| 0.9924 | 14.0 | 3150 | 1.0020 |
| 0.9882 | 15.0 | 3375 | 0.9802 |
| 0.9836 | 16.0 | 3600 | 0.9773 |
| 0.9725 | 17.0 | 3825 | 0.9729 |
| 0.9633 | 18.0 | 4050 | 0.9558 |
| 0.9601 | 19.0 | 4275 | 0.9707 |
| 0.9553 | 20.0 | 4500 | 0.9555 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
