Baljinnyam
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update model card README.md
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README.md
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---
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language:
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- mn
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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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# bloom-NER-fr
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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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---
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language:
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- mn
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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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# bloom-NER-fr
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This model is a fine-tuned version of [roberta-large-mnli](https://huggingface.co/roberta-large-mnli) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2930
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- Precision: 0.5423
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- Recall: 0.6361
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- F1: 0.5854
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- Accuracy: 0.9004
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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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| 0.7569 | 1.0 | 47 | 0.4836 | 0.3709 | 0.3924 | 0.3813 | 0.8604 |
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| 0.4348 | 2.0 | 94 | 0.3771 | 0.4395 | 0.5443 | 0.4863 | 0.8687 |
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| 0.3607 | 3.0 | 141 | 0.3232 | 0.5115 | 0.6086 | 0.5559 | 0.8953 |
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| 0.2913 | 4.0 | 188 | 0.2918 | 0.5527 | 0.6255 | 0.5868 | 0.8974 |
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| 0.2602 | 5.0 | 235 | 0.2835 | 0.5485 | 0.6445 | 0.5926 | 0.9028 |
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| 0.2332 | 6.0 | 282 | 0.2930 | 0.5423 | 0.6361 | 0.5854 | 0.9004 |
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### Framework versions
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