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README.md
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---
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license:
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tags:
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- generated_from_trainer
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metrics:
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# medlid-identify
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This model is a fine-tuned version of [
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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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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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### Framework versions
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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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# medlid-identify
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1248
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- Precision: 0.4410
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- Recall: 0.4209
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- F1: 0.4307
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- Accuracy: 0.9541
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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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| No log | 1.0 | 381 | 0.1297 | 0.3898 | 0.3032 | 0.3411 | 0.9525 |
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| 0.1774 | 2.0 | 762 | 0.1191 | 0.4485 | 0.3489 | 0.3925 | 0.9551 |
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| 0.1177 | 3.0 | 1143 | 0.1216 | 0.4341 | 0.4209 | 0.4274 | 0.9544 |
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| 0.0974 | 4.0 | 1524 | 0.1248 | 0.4410 | 0.4209 | 0.4307 | 0.9541 |
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### Framework versions
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