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README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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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:
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- Accuracy: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 57 | 0.
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| No log | 2.0 | 114 | 0.
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| No log | 3.0 | 171 | 0.
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| No log | 4.0 | 228 | 0.
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| No log | 5.0 | 285 | 0.
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| No log | 6.0 | 342 | 0.
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| No log | 7.0 | 399 |
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| No log | 8.0 | 456 |
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| 0.
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| 0.
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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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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: 0.9163
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- Accuracy: 0.7
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 57 | 0.9288 | 0.56 |
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| No log | 2.0 | 114 | 0.8651 | 0.58 |
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| No log | 3.0 | 171 | 0.8420 | 0.68 |
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| No log | 4.0 | 228 | 0.8642 | 0.64 |
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| No log | 5.0 | 285 | 0.8165 | 0.68 |
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| No log | 6.0 | 342 | 0.8293 | 0.72 |
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| No log | 7.0 | 399 | 0.8527 | 0.66 |
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| No log | 8.0 | 456 | 0.9009 | 0.7 |
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| 0.5624 | 9.0 | 513 | 0.8983 | 0.7 |
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| 0.5624 | 10.0 | 570 | 0.9163 | 0.7 |
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### Framework versions
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pytorch_model.bin
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