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distilbert-base-uncased-PINA-dfnew-2
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3815
- Accuracy: 0.9106
- Precision: 0.7799
- Recall: 0.7804
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 | Precision | Recall |
---|---|---|---|---|---|---|
1.5008 | 1.0 | 1002 | 0.6541 | 0.8482 | 0.6999 | 0.6173 |
0.4599 | 2.0 | 2004 | 0.4240 | 0.9004 | 0.7739 | 0.7641 |
0.2458 | 3.0 | 3006 | 0.3815 | 0.9106 | 0.7799 | 0.7804 |
0.1549 | 4.0 | 4008 | 0.3817 | 0.9206 | 0.8114 | 0.8064 |
0.0977 | 5.0 | 5010 | 0.4187 | 0.9194 | 0.8118 | 0.8031 |
0.0662 | 6.0 | 6012 | 0.4207 | 0.9213 | 0.8109 | 0.8085 |
0.0454 | 7.0 | 7014 | 0.4361 | 0.9226 | 0.8276 | 0.8199 |
0.0314 | 8.0 | 8016 | 0.4562 | 0.9233 | 0.8288 | 0.8209 |
0.023 | 9.0 | 9018 | 0.4657 | 0.9221 | 0.8272 | 0.8192 |
0.0185 | 10.0 | 10020 | 0.4620 | 0.9226 | 0.8278 | 0.8191 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3