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loha_fine_tuned_copa_XLMroberta

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README.md CHANGED
@@ -19,9 +19,9 @@ 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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- - Loss: 0.6941
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- - Accuracy: 0.46
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- - F1: 0.4587
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  ## Model description
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@@ -40,7 +40,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.003
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -52,14 +52,14 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.7175 | 1.0 | 50 | 0.6927 | 0.52 | 0.5173 |
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- | 0.6883 | 2.0 | 100 | 0.6942 | 0.48 | 0.4788 |
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- | 0.7067 | 3.0 | 150 | 0.6932 | 0.5 | 0.5 |
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- | 0.6896 | 4.0 | 200 | 0.6936 | 0.48 | 0.4808 |
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- | 0.7076 | 5.0 | 250 | 0.6934 | 0.47 | 0.4679 |
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- | 0.6942 | 6.0 | 300 | 0.6936 | 0.48 | 0.4800 |
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- | 0.6908 | 7.0 | 350 | 0.6939 | 0.47 | 0.4679 |
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- | 0.6953 | 8.0 | 400 | 0.6941 | 0.46 | 0.4587 |
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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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+ - Loss: 0.6929
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+ - Accuracy: 0.57
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+ - F1: 0.5695
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.6981 | 1.0 | 50 | 0.6929 | 0.56 | 0.5589 |
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+ | 0.701 | 2.0 | 100 | 0.6929 | 0.56 | 0.5589 |
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+ | 0.6932 | 3.0 | 150 | 0.6929 | 0.57 | 0.5695 |
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+ | 0.6896 | 4.0 | 200 | 0.6929 | 0.57 | 0.5695 |
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+ | 0.6968 | 5.0 | 250 | 0.6929 | 0.57 | 0.5695 |
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+ | 0.6979 | 6.0 | 300 | 0.6929 | 0.57 | 0.5695 |
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+ | 0.6984 | 7.0 | 350 | 0.6929 | 0.57 | 0.5695 |
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+ | 0.6999 | 8.0 | 400 | 0.6929 | 0.57 | 0.5695 |
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  ### Framework versions
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