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bert-base-uncased-New_data_bert1
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9215
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.4496 | 1.0 | 2018 | 2.2066 |
| 2.2532 | 2.0 | 4036 | 2.1438 |
| 2.1572 | 3.0 | 6054 | 2.1046 |
| 2.0839 | 4.0 | 8072 | 2.0943 |
| 2.0222 | 5.0 | 10090 | 2.0573 |
| 1.9608 | 6.0 | 12108 | 2.0188 |
| 1.9123 | 7.0 | 14126 | 2.0008 |
| 1.8666 | 8.0 | 16144 | 2.0063 |
| 1.8305 | 9.0 | 18162 | 1.9607 |
| 1.7958 | 10.0 | 20180 | 1.9702 |
| 1.7498 | 11.0 | 22198 | 1.9635 |
| 1.7172 | 12.0 | 24216 | 1.9404 |
| 1.695 | 13.0 | 26234 | 1.9455 |
| 1.6628 | 14.0 | 28252 | 1.9269 |
| 1.6558 | 15.0 | 30270 | 1.9173 |
| 1.6293 | 16.0 | 32288 | 1.9215 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
