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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: Yepes_5e-05_29_03
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results: []
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# Yepes_5e-05_29_03
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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: 500
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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: Yepes_5e-05_29_03
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results: []
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# Yepes_5e-05_29_03
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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: 0.1549
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- Precision: 0.5725
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- Recall: 0.4261
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- F1: 0.4886
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- Accuracy: 0.9781
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## Model description
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- lr_scheduler_type: linear
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- training_steps: 500
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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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| 0.4799 | 5.0 | 25 | 0.1950 | 0.0 | 0.0 | 0.0 | 0.9697 |
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| 0.1703 | 10.0 | 50 | 0.1385 | 0.0 | 0.0 | 0.0 | 0.9697 |
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| 0.0981 | 15.0 | 75 | 0.1336 | 0.3361 | 0.2273 | 0.2712 | 0.9740 |
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| 0.0594 | 20.0 | 100 | 0.1192 | 0.4150 | 0.3466 | 0.3777 | 0.9757 |
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| 0.0318 | 25.0 | 125 | 0.1293 | 0.5039 | 0.3693 | 0.4262 | 0.9775 |
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| 0.0177 | 30.0 | 150 | 0.1303 | 0.5123 | 0.4716 | 0.4911 | 0.9767 |
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| 0.0114 | 35.0 | 175 | 0.1363 | 0.5411 | 0.4489 | 0.4907 | 0.9773 |
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| 0.0074 | 40.0 | 200 | 0.1459 | 0.5455 | 0.4773 | 0.5091 | 0.9774 |
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| 0.0058 | 45.0 | 225 | 0.1442 | 0.5190 | 0.4659 | 0.4910 | 0.9767 |
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| 0.0044 | 50.0 | 250 | 0.1549 | 0.5725 | 0.4261 | 0.4886 | 0.9781 |
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### Framework versions
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- Transformers 4.27.4
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