---
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: 0.5876
- Accuracy: 0.7
- F1: 0.7002

## 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 |
| 0.8238        | 2.0   | 208  | 0.7232          | 0.654    | 0.6532 |
| 0.787         | 3.0   | 312  | 0.7135          | 0.66     | 0.6543 |
| 0.7555        | 4.0   | 416  | 0.6902          | 0.682    | 0.6801 |
| 0.7369        | 5.0   | 520  | 0.6555          | 0.7      | 0.7005 |
| 0.7163        | 6.0   | 624  | 0.6495          | 0.7      | 0.6994 |
| 0.7028        | 7.0   | 728  | 0.6438          | 0.708    | 0.7080 |
| 0.6914        | 8.0   | 832  | 0.6087          | 0.698    | 0.6972 |
| 0.6761        | 9.0   | 936  | 0.6039          | 0.7      | 0.6995 |
| 0.6676        | 10.0  | 1040 | 0.6042          | 0.692    | 0.6911 |
| 0.6572        | 11.0  | 1144 | 0.6019          | 0.704    | 0.7033 |
| 0.6527        | 12.0  | 1248 | 0.5927          | 0.712    | 0.7126 |
| 0.6364        | 13.0  | 1352 | 0.5951          | 0.708    | 0.7086 |
| 0.6387        | 14.0  | 1456 | 0.5917          | 0.688    | 0.6864 |
| 0.6326        | 15.0  | 1560 | 0.5870          | 0.71     | 0.7105 |
| 0.6199        | 16.0  | 1664 | 0.5944          | 0.696    | 0.6942 |
| 0.6107        | 17.0  | 1768 | 0.5850          | 0.714    | 0.7145 |
| 0.6118        | 18.0  | 1872 | 0.5853          | 0.716    | 0.7168 |
| 0.6083        | 19.0  | 1976 | 0.5895          | 0.704    | 0.7037 |
| 0.5946        | 20.0  | 2080 | 0.5876          | 0.7      | 0.7002 |


### Framework versions

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