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README.md
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This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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- Accuracy: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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### Framework versions
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This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0824
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- Precision: 0.7891
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- Recall: 0.7470
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- F1: 0.7675
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- Accuracy: 0.9741
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.4311 | 0.96 | 25 | 0.1785 | 0.7 | 0.0120 | 0.0237 | 0.9354 |
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| 0.1235 | 1.92 | 50 | 0.0961 | 0.6732 | 0.7091 | 0.6907 | 0.9655 |
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| 0.0749 | 2.88 | 75 | 0.0858 | 0.6801 | 0.8417 | 0.7523 | 0.9692 |
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| 0.063 | 3.85 | 100 | 0.0857 | 0.6764 | 0.8744 | 0.7628 | 0.9666 |
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| 0.0521 | 4.81 | 125 | 0.0757 | 0.7419 | 0.7522 | 0.7470 | 0.9723 |
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| 0.0336 | 5.77 | 150 | 0.0829 | 0.7170 | 0.7935 | 0.7533 | 0.9714 |
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| 0.0287 | 6.73 | 175 | 0.0824 | 0.7891 | 0.7470 | 0.7675 | 0.9741 |
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### Framework versions
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