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Training in progress epoch 0

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README.md CHANGED
@@ -15,13 +15,13 @@ 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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- - Train Loss: 0.7464
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- - Train End Logits Accuracy: 0.8000
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- - Train Start Logits Accuracy: 0.8410
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- - Validation Loss: 0.4623
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- - Validation End Logits Accuracy: 0.8531
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- - Validation Start Logits Accuracy: 0.9049
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- - Epoch: 2
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  ## Model description
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@@ -47,9 +47,7 @@ The following hyperparameters were used during training:
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  | Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
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  |:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
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- | 1.7971 | 0.5734 | 0.6205 | 0.5606 | 0.8322 | 0.8713 | 0 |
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- | 0.9966 | 0.7425 | 0.7857 | 0.4648 | 0.8559 | 0.8993 | 1 |
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- | 0.7464 | 0.8000 | 0.8410 | 0.4623 | 0.8531 | 0.9049 | 2 |
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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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+ - Train Loss: 1.7701
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+ - Train End Logits Accuracy: 0.5788
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+ - Train Start Logits Accuracy: 0.6180
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+ - Validation Loss: 0.5240
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+ - Validation End Logits Accuracy: 0.8406
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+ - Validation Start Logits Accuracy: 0.8811
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+ - Epoch: 0
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  ## Model description
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  | Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
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  |:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
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+ | 1.7701 | 0.5788 | 0.6180 | 0.5240 | 0.8406 | 0.8811 | 0 |
 
 
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  ### Framework versions
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