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ThuyNT03
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xlm-roberta-base-Balance_VietNam-aug_swap

Text Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
Inference Endpoints
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  1. README.md +12 -12
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -18,9 +18,9 @@ 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 the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6092
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- - Accuracy: 0.66
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- - F1: 0.6719
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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: 5e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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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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- | 1.0488 | 1.0 | 86 | 0.9674 | 0.64 | 0.5483 |
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- | 0.8757 | 2.0 | 172 | 0.9354 | 0.63 | 0.5882 |
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- | 0.7429 | 3.0 | 258 | 0.7688 | 0.71 | 0.7082 |
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- | 0.5999 | 4.0 | 344 | 0.8059 | 0.66 | 0.6722 |
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- | 0.3956 | 5.0 | 430 | 1.0663 | 0.71 | 0.7209 |
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- | 0.2597 | 6.0 | 516 | 1.3475 | 0.7 | 0.7060 |
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- | 0.1618 | 7.0 | 602 | 1.4573 | 0.67 | 0.6796 |
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- | 0.112 | 8.0 | 688 | 1.6092 | 0.66 | 0.6719 |
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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 the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.2667
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+ - Accuracy: 0.69
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+ - F1: 0.6959
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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: 16
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  - eval_batch_size: 16
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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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+ | 0.9608 | 1.0 | 86 | 0.7778 | 0.63 | 0.5729 |
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+ | 0.6733 | 2.0 | 172 | 0.7087 | 0.68 | 0.6835 |
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+ | 0.4889 | 3.0 | 258 | 0.7707 | 0.7 | 0.7028 |
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+ | 0.3672 | 4.0 | 344 | 0.7906 | 0.69 | 0.7021 |
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+ | 0.2388 | 5.0 | 430 | 1.0683 | 0.7 | 0.6979 |
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+ | 0.1691 | 6.0 | 516 | 1.1391 | 0.69 | 0.7010 |
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+ | 0.1323 | 7.0 | 602 | 1.2486 | 0.71 | 0.7176 |
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+ | 0.1033 | 8.0 | 688 | 1.2667 | 0.69 | 0.6959 |
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  ### Framework versions
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