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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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End of training

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  1. README.md +23 -23
  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: 0.5890
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  - Accuracy: 0.698
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- - F1: 0.6983
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  ## Model description
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@@ -39,7 +39,7 @@ More information needed
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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: 32
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  - eval_batch_size: 32
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  - seed: 42
@@ -51,26 +51,26 @@ 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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- | 0.787 | 3.0 | 312 | 0.7133 | 0.658 | 0.6521 |
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- | 0.7552 | 4.0 | 416 | 0.6904 | 0.68 | 0.6780 |
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- | 0.7366 | 5.0 | 520 | 0.6555 | 0.704 | 0.7045 |
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- | 0.7158 | 6.0 | 624 | 0.6500 | 0.7 | 0.6994 |
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- | 0.7025 | 7.0 | 728 | 0.6429 | 0.71 | 0.7101 |
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- | 0.6912 | 8.0 | 832 | 0.6097 | 0.698 | 0.6972 |
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- | 0.6764 | 9.0 | 936 | 0.6033 | 0.7 | 0.6996 |
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- | 0.667 | 10.0 | 1040 | 0.6040 | 0.69 | 0.6886 |
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- | 0.6571 | 11.0 | 1144 | 0.6022 | 0.702 | 0.7011 |
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- | 0.6532 | 12.0 | 1248 | 0.5941 | 0.71 | 0.7107 |
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- | 0.6369 | 13.0 | 1352 | 0.5956 | 0.706 | 0.7066 |
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- | 0.6385 | 14.0 | 1456 | 0.5929 | 0.688 | 0.6864 |
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- | 0.6328 | 15.0 | 1560 | 0.5880 | 0.708 | 0.7085 |
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- | 0.6199 | 16.0 | 1664 | 0.5956 | 0.69 | 0.6885 |
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- | 0.6109 | 17.0 | 1768 | 0.5865 | 0.712 | 0.7125 |
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- | 0.6116 | 18.0 | 1872 | 0.5863 | 0.716 | 0.7169 |
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- | 0.6092 | 19.0 | 1976 | 0.5908 | 0.704 | 0.7037 |
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- | 0.594 | 20.0 | 2080 | 0.5890 | 0.698 | 0.6983 |
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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: 0.6107
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  - Accuracy: 0.698
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+ - F1: 0.6968
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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: 1e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
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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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+ | 1.06 | 1.0 | 104 | 0.8187 | 0.61 | 0.6100 |
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+ | 0.849 | 2.0 | 208 | 0.7525 | 0.642 | 0.6415 |
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+ | 0.8117 | 3.0 | 312 | 0.7479 | 0.616 | 0.6044 |
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+ | 0.7758 | 4.0 | 416 | 0.7269 | 0.652 | 0.6490 |
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+ | 0.7638 | 5.0 | 520 | 0.6960 | 0.674 | 0.6741 |
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+ | 0.7412 | 6.0 | 624 | 0.6842 | 0.676 | 0.6739 |
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+ | 0.7337 | 7.0 | 728 | 0.6653 | 0.692 | 0.6922 |
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+ | 0.723 | 8.0 | 832 | 0.6502 | 0.674 | 0.6711 |
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+ | 0.7045 | 9.0 | 936 | 0.6407 | 0.672 | 0.6681 |
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+ | 0.6975 | 10.0 | 1040 | 0.6330 | 0.686 | 0.6852 |
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+ | 0.6914 | 11.0 | 1144 | 0.6351 | 0.686 | 0.6846 |
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+ | 0.6876 | 12.0 | 1248 | 0.6230 | 0.702 | 0.7023 |
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+ | 0.672 | 13.0 | 1352 | 0.6230 | 0.698 | 0.6978 |
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+ | 0.6733 | 14.0 | 1456 | 0.6251 | 0.678 | 0.6736 |
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+ | 0.6701 | 15.0 | 1560 | 0.6124 | 0.706 | 0.7064 |
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+ | 0.6592 | 16.0 | 1664 | 0.6195 | 0.688 | 0.6853 |
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+ | 0.6534 | 17.0 | 1768 | 0.6070 | 0.708 | 0.7082 |
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+ | 0.6528 | 18.0 | 1872 | 0.6093 | 0.704 | 0.7040 |
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+ | 0.6514 | 19.0 | 1976 | 0.6124 | 0.698 | 0.6963 |
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+ | 0.6406 | 20.0 | 2080 | 0.6107 | 0.698 | 0.6968 |
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  ### Framework versions
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