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eunyounglee
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degree-bert-finetuning-2

Text Classification
Transformers
PyTorch
Safetensors
bert
Generated from Trainer
Inference Endpoints
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eunyounglee commited on
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End of training

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  1. README.md +22 -22
  2. model.safetensors +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 [klue/bert-base](https://huggingface.co/klue/bert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5866
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- - Accuracy: 0.702
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- - F1: 0.7023
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  ## Model description
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@@ -52,25 +52,25 @@ 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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  | 0.9822 | 1.0 | 104 | 0.7872 | 0.638 | 0.6374 |
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- | 0.8237 | 2.0 | 208 | 0.7235 | 0.656 | 0.6552 |
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- | 0.7869 | 3.0 | 312 | 0.7140 | 0.658 | 0.6521 |
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- | 0.755 | 4.0 | 416 | 0.6894 | 0.678 | 0.6762 |
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- | 0.7368 | 5.0 | 520 | 0.6562 | 0.7 | 0.7004 |
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- | 0.7164 | 6.0 | 624 | 0.6501 | 0.696 | 0.6951 |
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- | 0.7032 | 7.0 | 728 | 0.6437 | 0.708 | 0.7084 |
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- | 0.6911 | 8.0 | 832 | 0.6097 | 0.694 | 0.6930 |
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- | 0.6759 | 9.0 | 936 | 0.6034 | 0.702 | 0.7019 |
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- | 0.6671 | 10.0 | 1040 | 0.6038 | 0.69 | 0.6890 |
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- | 0.6573 | 11.0 | 1144 | 0.6016 | 0.704 | 0.7033 |
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- | 0.653 | 12.0 | 1248 | 0.5920 | 0.712 | 0.7126 |
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- | 0.6364 | 13.0 | 1352 | 0.5950 | 0.708 | 0.7085 |
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- | 0.6386 | 14.0 | 1456 | 0.5922 | 0.688 | 0.6864 |
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- | 0.6321 | 15.0 | 1560 | 0.5853 | 0.71 | 0.7105 |
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- | 0.6193 | 16.0 | 1664 | 0.5936 | 0.69 | 0.6889 |
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- | 0.6109 | 17.0 | 1768 | 0.5838 | 0.714 | 0.7145 |
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- | 0.612 | 18.0 | 1872 | 0.5838 | 0.716 | 0.7168 |
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- | 0.6083 | 19.0 | 1976 | 0.5884 | 0.708 | 0.7077 |
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- | 0.5948 | 20.0 | 2080 | 0.5866 | 0.702 | 0.7023 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5876
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+ - Accuracy: 0.7
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+ - F1: 0.7002
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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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  | 0.9822 | 1.0 | 104 | 0.7872 | 0.638 | 0.6374 |
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+ | 0.8238 | 2.0 | 208 | 0.7232 | 0.654 | 0.6532 |
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+ | 0.787 | 3.0 | 312 | 0.7135 | 0.66 | 0.6543 |
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+ | 0.7555 | 4.0 | 416 | 0.6902 | 0.682 | 0.6801 |
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+ | 0.7369 | 5.0 | 520 | 0.6555 | 0.7 | 0.7005 |
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+ | 0.7163 | 6.0 | 624 | 0.6495 | 0.7 | 0.6994 |
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+ | 0.7028 | 7.0 | 728 | 0.6438 | 0.708 | 0.7080 |
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+ | 0.6914 | 8.0 | 832 | 0.6087 | 0.698 | 0.6972 |
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+ | 0.6761 | 9.0 | 936 | 0.6039 | 0.7 | 0.6995 |
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+ | 0.6676 | 10.0 | 1040 | 0.6042 | 0.692 | 0.6911 |
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+ | 0.6572 | 11.0 | 1144 | 0.6019 | 0.704 | 0.7033 |
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+ | 0.6527 | 12.0 | 1248 | 0.5927 | 0.712 | 0.7126 |
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+ | 0.6364 | 13.0 | 1352 | 0.5951 | 0.708 | 0.7086 |
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+ | 0.6387 | 14.0 | 1456 | 0.5917 | 0.688 | 0.6864 |
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+ | 0.6326 | 15.0 | 1560 | 0.5870 | 0.71 | 0.7105 |
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+ | 0.6199 | 16.0 | 1664 | 0.5944 | 0.696 | 0.6942 |
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+ | 0.6107 | 17.0 | 1768 | 0.5850 | 0.714 | 0.7145 |
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+ | 0.6118 | 18.0 | 1872 | 0.5853 | 0.716 | 0.7168 |
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+ | 0.6083 | 19.0 | 1976 | 0.5895 | 0.704 | 0.7037 |
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+ | 0.5946 | 20.0 | 2080 | 0.5876 | 0.7 | 0.7002 |
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  ### Framework versions
model.safetensors CHANGED
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