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--- |
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license: cc-by-sa-4.0 |
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base_model: klue/bert-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: degree-bert-finetuning-2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# degree-bert-finetuning-2 |
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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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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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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 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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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 |
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- Transformers 4.38.1 |
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- Pytorch 2.2.0 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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