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my_new_model
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4151
- Accuracy: 0.882
- F1: 0.8815
- Precision: 0.8825
- Recall: 0.882
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 125 | 0.5276 | 0.846 | 0.8496 | 0.8591 | 0.846 |
| No log | 2.0 | 250 | 0.3993 | 0.874 | 0.8755 | 0.8801 | 0.874 |
| No log | 3.0 | 375 | 0.3623 | 0.878 | 0.8808 | 0.8896 | 0.878 |
| 0.5033 | 4.0 | 500 | 0.3386 | 0.898 | 0.8985 | 0.9005 | 0.898 |
| 0.5033 | 5.0 | 625 | 0.3791 | 0.884 | 0.8840 | 0.8850 | 0.884 |
| 0.5033 | 6.0 | 750 | 0.3490 | 0.898 | 0.8993 | 0.9020 | 0.898 |
| 0.5033 | 7.0 | 875 | 0.3899 | 0.89 | 0.8898 | 0.8897 | 0.89 |
| 0.1244 | 8.0 | 1000 | 0.4148 | 0.87 | 0.8690 | 0.8686 | 0.87 |
| 0.1244 | 9.0 | 1125 | 0.4030 | 0.888 | 0.8880 | 0.8887 | 0.888 |
| 0.1244 | 10.0 | 1250 | 0.4151 | 0.882 | 0.8815 | 0.8825 | 0.882 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
