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ThuyNT03
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PhoBERT-cls-OCR

Text Classification
Transformers
PyTorch
roberta
Generated from Trainer
Inference Endpoints
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Training completed!

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  1. README.md +11 -11
  2. pytorch_model.bin +1 -1
  3. training_args.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: 0.1323
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- - Accuracy: 0.9722
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- - F1: 0.9722
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  ## Model description
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@@ -50,14 +50,14 @@ 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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- | 0.6246 | 1.0 | 18 | 0.5147 | 0.6667 | 0.5774 |
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- | 0.4585 | 2.0 | 36 | 0.3251 | 0.9028 | 0.9024 |
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- | 0.3096 | 3.0 | 54 | 0.2166 | 0.9306 | 0.9311 |
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- | 0.2149 | 4.0 | 72 | 0.1609 | 0.9583 | 0.9585 |
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- | 0.1154 | 5.0 | 90 | 0.1350 | 0.9722 | 0.9722 |
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- | 0.1185 | 6.0 | 108 | 0.1772 | 0.9444 | 0.9440 |
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- | 0.0747 | 7.0 | 126 | 0.1379 | 0.9722 | 0.9722 |
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- | 0.0662 | 8.0 | 144 | 0.1323 | 0.9722 | 0.9722 |
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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: 0.1546
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+ - Accuracy: 0.9593
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+ - F1: 0.9592
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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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+ | 0.4221 | 1.0 | 43 | 0.2568 | 0.9070 | 0.9049 |
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+ | 0.1993 | 2.0 | 86 | 0.1515 | 0.9593 | 0.9592 |
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+ | 0.1313 | 3.0 | 129 | 0.1582 | 0.9593 | 0.9591 |
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+ | 0.0966 | 4.0 | 172 | 0.1456 | 0.9651 | 0.9651 |
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+ | 0.0737 | 5.0 | 215 | 0.1432 | 0.9651 | 0.9651 |
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+ | 0.0592 | 6.0 | 258 | 0.1488 | 0.9651 | 0.9651 |
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+ | 0.0633 | 7.0 | 301 | 0.1605 | 0.9593 | 0.9592 |
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+ | 0.0575 | 8.0 | 344 | 0.1546 | 0.9593 | 0.9592 |
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  ### Framework versions
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