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CancerTextV1
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: 0.5476
- Accuracy: 0.8683
- Precision: 0.8558
- Recall: 0.8870
- F1: 0.8711
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: 1e-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
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.3268 | 1.0 | 600 | 0.3939 | 0.8475 | 0.8268 | 0.8804 | 0.8528 |
0.3132 | 2.0 | 1200 | 0.3510 | 0.8475 | 0.8509 | 0.8439 | 0.8474 |
0.2595 | 3.0 | 1800 | 0.3631 | 0.8617 | 0.8505 | 0.8787 | 0.8644 |
0.2256 | 4.0 | 2400 | 0.4303 | 0.8625 | 0.8507 | 0.8804 | 0.8653 |
0.1944 | 5.0 | 3000 | 0.4551 | 0.8642 | 0.8592 | 0.8721 | 0.8656 |
0.1734 | 6.0 | 3600 | 0.4673 | 0.86 | 0.8434 | 0.8854 | 0.8639 |
0.1446 | 7.0 | 4200 | 0.4960 | 0.87 | 0.8562 | 0.8904 | 0.8730 |
0.1371 | 8.0 | 4800 | 0.5162 | 0.8708 | 0.8646 | 0.8804 | 0.8724 |
0.123 | 9.0 | 5400 | 0.5396 | 0.8642 | 0.8604 | 0.8704 | 0.8654 |
0.1174 | 10.0 | 6000 | 0.5476 | 0.8683 | 0.8558 | 0.8870 | 0.8711 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1