bert-finetuned-preven
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: 0.1547
- Mse: 0.1547
- Mae: 0.0372
- R2: 0.8452
- Accuracy: 0.9879
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.8278 | 1.0 | 950 | 0.3087 | 0.3087 | 0.0722 | 0.6911 | 0.9783 |
| 0.2563 | 2.0 | 1900 | 0.1785 | 0.1785 | 0.0575 | 0.8214 | 0.9845 |
| 0.1446 | 3.0 | 2850 | 0.1547 | 0.1547 | 0.0372 | 0.8452 | 0.9879 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
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