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bert-base-cased-finetuned-dob
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3693
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: 10
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
8.4072 | 1.0 | 26 | 6.4498 |
5.8926 | 2.0 | 52 | 4.5400 |
4.4943 | 3.0 | 78 | 3.4040 |
3.6156 | 4.0 | 104 | 2.6775 |
3.0402 | 5.0 | 130 | 2.1847 |
2.6294 | 6.0 | 156 | 1.8491 |
2.3366 | 7.0 | 182 | 1.6251 |
2.147 | 8.0 | 208 | 1.4801 |
2.0068 | 9.0 | 234 | 1.3981 |
1.9378 | 10.0 | 260 | 1.3693 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1