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Arron99
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tes1-UASNLP2

Text Classification
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bert
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End of training

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  1. README.md +13 -13
  2. model.safetensors +1 -1
  3. runs/Jun29_08-47-46_a08fdfbf1ec7/events.out.tfevents.1719650867.a08fdfbf1ec7.1604.4 +3 -0
  4. runs/Jun29_08-47-46_a08fdfbf1ec7/events.out.tfevents.1719652308.a08fdfbf1ec7.1604.5 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3497
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- - Accuracy: 0.8732
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- - Precision: 0.8735
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- - Recall: 0.9022
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- - F1: 0.8876
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  ## Model description
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@@ -58,14 +58,14 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 0.4694 | 1.2121 | 100 | 0.3865 | 0.8459 | 0.8288 | 0.9104 | 0.8677 |
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- | 0.2551 | 2.4242 | 200 | 0.3497 | 0.8732 | 0.8735 | 0.9022 | 0.8876 |
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- | 0.1637 | 3.6364 | 300 | 0.4273 | 0.8648 | 0.8426 | 0.9302 | 0.8843 |
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- | 0.1013 | 4.8485 | 400 | 0.4728 | 0.8759 | 0.8863 | 0.8906 | 0.8884 |
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- | 0.0656 | 6.0606 | 500 | 0.5119 | 0.8740 | 0.9053 | 0.8632 | 0.8838 |
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- | 0.0445 | 7.2727 | 600 | 0.5829 | 0.8732 | 0.8852 | 0.8865 | 0.8859 |
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- | 0.029 | 8.4848 | 700 | 0.6224 | 0.8747 | 0.8809 | 0.8953 | 0.8881 |
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- | 0.0188 | 9.6970 | 800 | 0.6621 | 0.8751 | 0.8744 | 0.9049 | 0.8894 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3413
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+ - Accuracy: 0.8705
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+ - Precision: 0.8858
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+ - Recall: 0.8803
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+ - F1: 0.8830
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.4596 | 1.2121 | 100 | 0.3631 | 0.8554 | 0.8767 | 0.8605 | 0.8685 |
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+ | 0.254 | 2.4242 | 200 | 0.3413 | 0.8705 | 0.8858 | 0.8803 | 0.8830 |
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+ | 0.1674 | 3.6364 | 300 | 0.3847 | 0.8793 | 0.8758 | 0.9118 | 0.8934 |
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+ | 0.0968 | 4.8485 | 400 | 0.4927 | 0.8759 | 0.9145 | 0.8564 | 0.8845 |
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+ | 0.0614 | 6.0606 | 500 | 0.5308 | 0.8721 | 0.8748 | 0.8981 | 0.8863 |
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+ | 0.0418 | 7.2727 | 600 | 0.6098 | 0.8759 | 0.8988 | 0.8748 | 0.8867 |
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+ | 0.0296 | 8.4848 | 700 | 0.6507 | 0.8751 | 0.8910 | 0.8830 | 0.8870 |
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+ | 0.0183 | 9.6970 | 800 | 0.6822 | 0.8789 | 0.8944 | 0.8865 | 0.8904 |
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  ### Framework versions
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