---
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