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ThuyNT03
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PhoBERT-Final_Mixed-aug_insert_synonym-2

Text Classification
Transformers
PyTorch
roberta
Generated from Trainer
Inference Endpoints
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  1. README.md +10 -10
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -17,9 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3778
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  - Accuracy: 0.69
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- - F1: 0.6996
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.8712 | 1.0 | 87 | 0.8232 | 0.68 | 0.6467 |
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- | 0.5648 | 2.0 | 174 | 0.6551 | 0.76 | 0.7591 |
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- | 0.3706 | 3.0 | 261 | 0.7835 | 0.72 | 0.7263 |
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- | 0.2256 | 4.0 | 348 | 0.9157 | 0.7 | 0.7107 |
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- | 0.1558 | 5.0 | 435 | 1.0868 | 0.71 | 0.7215 |
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- | 0.1266 | 6.0 | 522 | 1.2840 | 0.71 | 0.7185 |
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- | 0.0869 | 7.0 | 609 | 1.3645 | 0.71 | 0.7185 |
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- | 0.0866 | 8.0 | 696 | 1.3778 | 0.69 | 0.6996 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.2465
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  - Accuracy: 0.69
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+ - F1: 0.6880
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.9109 | 1.0 | 88 | 0.8214 | 0.65 | 0.6425 |
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+ | 0.6223 | 2.0 | 176 | 0.6999 | 0.7 | 0.7021 |
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+ | 0.424 | 3.0 | 264 | 0.7126 | 0.73 | 0.7305 |
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+ | 0.2932 | 4.0 | 352 | 0.8673 | 0.72 | 0.7172 |
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+ | 0.1692 | 5.0 | 440 | 1.0126 | 0.68 | 0.6806 |
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+ | 0.1192 | 6.0 | 528 | 1.1561 | 0.69 | 0.6889 |
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+ | 0.067 | 7.0 | 616 | 1.2002 | 0.68 | 0.6835 |
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+ | 0.0481 | 8.0 | 704 | 1.2465 | 0.69 | 0.6880 |
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  ### Framework versions
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