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- README.md +13 -13
- pytorch_model.bin +1 -1
- runs/Sep12_21-41-31_8d8e5e6b31d0/events.out.tfevents.1631483814.8d8e5e6b31d0.88.8 +3 -0
- runs/Sep12_21-56-56_8d8e5e6b31d0/1631483821.55237/events.out.tfevents.1631483821.8d8e5e6b31d0.88.10 +3 -0
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- training_args.bin +1 -1
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 [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) 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 |
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| No log | 3.0 | 171 |
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| No log | 4.0 | 228 |
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| No log | 5.0 | 285 |
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| No log | 6.0 | 342 |
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| No log | 7.0 | 399 |
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| No log | 8.0 | 456 |
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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: 0.5
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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 [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.0553
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- Accuracy: 0.5
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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 | 0.9749 | 0.42 |
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| No log | 2.0 | 114 | 1.1263 | 0.46 |
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| No log | 3.0 | 171 | 1.2782 | 0.5 |
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| No log | 4.0 | 228 | 1.8247 | 0.54 |
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| No log | 5.0 | 285 | 2.3015 | 0.5 |
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| No log | 6.0 | 342 | 2.6150 | 0.5 |
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| No log | 7.0 | 399 | 2.7772 | 0.5 |
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| No log | 8.0 | 456 | 2.9284 | 0.5 |
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| 0.3569 | 9.0 | 513 | 3.0202 | 0.5 |
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| 0.3569 | 10.0 | 570 | 3.0553 | 0.5 |
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### Framework versions
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pytorch_model.bin
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