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README.md
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license: mit
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tags:
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- generated_from_trainer
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model-index:
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- name: tmvar_5e-05_ES2
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results: []
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# tmvar_5e-05_ES2
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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
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## Model description
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- lr_scheduler_type: linear
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- training_steps: 1000
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### Framework versions
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- Transformers 4.27.4
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: tmvar_5e-05_ES2
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results: []
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# tmvar_5e-05_ES2
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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: 0.0189
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- Precision: 0.8469
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- Recall: 0.8973
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- F1: 0.8714
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- Accuracy: 0.9971
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## Model description
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- lr_scheduler_type: linear
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- training_steps: 1000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.3852 | 1.47 | 25 | 0.1019 | 0.0 | 0.0 | 0.0 | 0.9843 |
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| 0.0775 | 2.94 | 50 | 0.0398 | 0.2812 | 0.3892 | 0.3265 | 0.9863 |
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| 0.0327 | 4.41 | 75 | 0.0243 | 0.4740 | 0.4919 | 0.4828 | 0.9910 |
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| 0.02 | 5.88 | 100 | 0.0191 | 0.7656 | 0.7946 | 0.7798 | 0.9954 |
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| 0.0084 | 7.35 | 125 | 0.0229 | 0.7766 | 0.7892 | 0.7828 | 0.9952 |
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| 0.0045 | 8.82 | 150 | 0.0172 | 0.8351 | 0.8486 | 0.8418 | 0.9964 |
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| 0.0023 | 10.29 | 175 | 0.0190 | 0.9148 | 0.8703 | 0.8920 | 0.9968 |
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| 0.0015 | 11.76 | 200 | 0.0189 | 0.8469 | 0.8973 | 0.8714 | 0.9971 |
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### Framework versions
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- Transformers 4.27.4
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