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---
license: cc-by-sa-4.0
base_model: klue/bert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: degree-bert-finetuning-2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# degree-bert-finetuning-2
This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5890
- Accuracy: 0.698
- F1: 0.6983
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9822 | 1.0 | 104 | 0.7872 | 0.638 | 0.6374 |
| 0.8237 | 2.0 | 208 | 0.7235 | 0.656 | 0.6552 |
| 0.787 | 3.0 | 312 | 0.7133 | 0.658 | 0.6521 |
| 0.7552 | 4.0 | 416 | 0.6904 | 0.68 | 0.6780 |
| 0.7366 | 5.0 | 520 | 0.6555 | 0.704 | 0.7045 |
| 0.7158 | 6.0 | 624 | 0.6500 | 0.7 | 0.6994 |
| 0.7025 | 7.0 | 728 | 0.6429 | 0.71 | 0.7101 |
| 0.6912 | 8.0 | 832 | 0.6097 | 0.698 | 0.6972 |
| 0.6764 | 9.0 | 936 | 0.6033 | 0.7 | 0.6996 |
| 0.667 | 10.0 | 1040 | 0.6040 | 0.69 | 0.6886 |
| 0.6571 | 11.0 | 1144 | 0.6022 | 0.702 | 0.7011 |
| 0.6532 | 12.0 | 1248 | 0.5941 | 0.71 | 0.7107 |
| 0.6369 | 13.0 | 1352 | 0.5956 | 0.706 | 0.7066 |
| 0.6385 | 14.0 | 1456 | 0.5929 | 0.688 | 0.6864 |
| 0.6328 | 15.0 | 1560 | 0.5880 | 0.708 | 0.7085 |
| 0.6199 | 16.0 | 1664 | 0.5956 | 0.69 | 0.6885 |
| 0.6109 | 17.0 | 1768 | 0.5865 | 0.712 | 0.7125 |
| 0.6116 | 18.0 | 1872 | 0.5863 | 0.716 | 0.7169 |
| 0.6092 | 19.0 | 1976 | 0.5908 | 0.704 | 0.7037 |
| 0.594 | 20.0 | 2080 | 0.5890 | 0.698 | 0.6983 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.2.0
- Datasets 2.17.1
- Tokenizers 0.15.2
|