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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: 0.5890 |
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- Accuracy: 0.698 |
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- F1: 0.6983 |
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## Model description |
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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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| 0.8237 | 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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- 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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