---
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: 0.6107
- Accuracy: 0.698
- F1: 0.6968

## 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: 1e-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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.06          | 1.0   | 104  | 0.8187          | 0.61     | 0.6100 |
| 0.849         | 2.0   | 208  | 0.7525          | 0.642    | 0.6415 |
| 0.8117        | 3.0   | 312  | 0.7479          | 0.616    | 0.6044 |
| 0.7758        | 4.0   | 416  | 0.7269          | 0.652    | 0.6490 |
| 0.7638        | 5.0   | 520  | 0.6960          | 0.674    | 0.6741 |
| 0.7412        | 6.0   | 624  | 0.6842          | 0.676    | 0.6739 |
| 0.7337        | 7.0   | 728  | 0.6653          | 0.692    | 0.6922 |
| 0.723         | 8.0   | 832  | 0.6502          | 0.674    | 0.6711 |
| 0.7045        | 9.0   | 936  | 0.6407          | 0.672    | 0.6681 |
| 0.6975        | 10.0  | 1040 | 0.6330          | 0.686    | 0.6852 |
| 0.6914        | 11.0  | 1144 | 0.6351          | 0.686    | 0.6846 |
| 0.6876        | 12.0  | 1248 | 0.6230          | 0.702    | 0.7023 |
| 0.672         | 13.0  | 1352 | 0.6230          | 0.698    | 0.6978 |
| 0.6733        | 14.0  | 1456 | 0.6251          | 0.678    | 0.6736 |
| 0.6701        | 15.0  | 1560 | 0.6124          | 0.706    | 0.7064 |
| 0.6592        | 16.0  | 1664 | 0.6195          | 0.688    | 0.6853 |
| 0.6534        | 17.0  | 1768 | 0.6070          | 0.708    | 0.7082 |
| 0.6528        | 18.0  | 1872 | 0.6093          | 0.704    | 0.7040 |
| 0.6514        | 19.0  | 1976 | 0.6124          | 0.698    | 0.6963 |
| 0.6406        | 20.0  | 2080 | 0.6107          | 0.698    | 0.6968 |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.0
- Datasets 2.17.1
- Tokenizers 0.15.2