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20230928-7-xlm-roberta-base-new

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xlm-roberta
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  1. README.md +23 -4
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Accuracy: 0.4491
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- - Loss: 3.1214
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  ## Model description
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@@ -49,8 +49,27 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Accuracy | Validation Loss |
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  |:-------------:|:-----:|:----:|:--------:|:---------------:|
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- | 4.0289 | 3.85 | 500 | 0.3558 | 3.5292 |
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- | 3.3398 | 7.69 | 1000 | 0.4491 | 3.1214 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Accuracy: 0.4740
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+ - Loss: nan
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  ## Model description
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  | Training Loss | Epoch | Step | Accuracy | Validation Loss |
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  |:-------------:|:-----:|:----:|:--------:|:---------------:|
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+ | 4.4628 | 0.46 | 200 | 0.3220 | nan |
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+ | 4.1552 | 0.91 | 400 | 0.3249 | nan |
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+ | 3.8537 | 1.37 | 600 | 0.3822 | nan |
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+ | 3.5294 | 1.82 | 800 | 0.3914 | 3.6973 |
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+ | 3.378 | 2.28 | 1000 | 0.3770 | 3.5247 |
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+ | 3.3717 | 2.73 | 1200 | 0.3795 | nan |
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+ | 3.3769 | 3.19 | 1400 | 0.4033 | 2.9623 |
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+ | 3.2682 | 3.64 | 1600 | 0.3975 | 3.3065 |
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+ | 3.3275 | 4.1 | 1800 | 0.4603 | 3.0879 |
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+ | 3.1686 | 4.56 | 2000 | 0.4385 | 2.8513 |
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+ | 3.1107 | 5.01 | 2200 | 0.4419 | nan |
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+ | 3.0418 | 5.47 | 2400 | 0.4372 | nan |
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+ | 2.9602 | 5.92 | 2600 | 0.4792 | 2.8451 |
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+ | 2.9038 | 6.38 | 2800 | 0.4772 | 2.7947 |
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+ | 2.8495 | 6.83 | 3000 | 0.415 | 2.9448 |
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+ | 2.9444 | 7.29 | 3200 | 0.4840 | nan |
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+ | 2.8306 | 7.74 | 3400 | 0.4806 | 2.3816 |
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+ | 2.8293 | 8.2 | 3600 | 0.4909 | 2.8671 |
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+ | 2.7785 | 8.66 | 3800 | 0.5377 | 2.6516 |
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+ | 2.7991 | 9.11 | 4000 | 0.5164 | nan |
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+ | 2.8131 | 9.57 | 4200 | 0.4740 | nan |
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  ### Framework versions
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