---
tags:
- generated_from_trainer
model-index:
- name: kobigbird-bert-base-finetuned-klue
  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. -->

# kobigbird-bert-base-finetuned-klue

This model is a fine-tuned version of [monologg/kobigbird-bert-base](https://huggingface.co/monologg/kobigbird-bert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9124

## 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: 5e-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: 60

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 5.1951        | 0.69  | 500   | 3.9518          |
| 3.7508        | 1.38  | 1000  | 3.4423          |
| 3.4379        | 2.07  | 1500  | 3.1397          |
| 3.1865        | 2.76  | 2000  | 2.8141          |
| 2.9852        | 3.45  | 2500  | 2.6055          |
| 2.7907        | 4.14  | 3000  | 2.4892          |
| 2.6985        | 4.83  | 3500  | 2.4130          |
| 2.63          | 5.52  | 4000  | 2.3479          |
| 2.5616        | 6.21  | 4500  | 2.3134          |
| 2.4898        | 6.9   | 5000  | 2.2526          |
| 2.4167        | 7.59  | 5500  | 2.2422          |
| 2.3861        | 8.28  | 6000  | 2.2138          |
| 2.3401        | 8.97  | 6500  | 2.1762          |
| 2.292         | 9.66  | 7000  | 2.1417          |
| 2.2705        | 10.34 | 7500  | 2.1148          |
| 2.2139        | 11.03 | 8000  | 2.1357          |
| 2.187         | 11.72 | 8500  | 2.0995          |
| 2.1518        | 12.41 | 9000  | 2.0554          |
| 2.1179        | 13.1  | 9500  | 2.0467          |
| 2.0781        | 13.79 | 10000 | 2.0418          |
| 2.0457        | 14.48 | 10500 | 2.0057          |
| 2.0326        | 15.17 | 11000 | 2.0022          |
| 1.9976        | 15.86 | 11500 | 2.0137          |
| 1.9602        | 16.55 | 12000 | 1.9703          |
| 1.9435        | 17.24 | 12500 | 1.9920          |
| 1.9092        | 17.93 | 13000 | 1.9504          |
| 1.8714        | 18.62 | 13500 | 1.9731          |
| 1.8715        | 19.31 | 14000 | 1.9471          |
| 1.8824        | 20.0  | 14500 | 1.9462          |
| 1.8261        | 20.69 | 15000 | 1.9412          |
| 1.815         | 21.38 | 15500 | 1.9308          |
| 1.7988        | 22.07 | 16000 | 1.9285          |
| 1.7722        | 22.76 | 16500 | 1.9341          |
| 1.7606        | 23.45 | 17000 | 1.9007          |
| 1.7402        | 24.14 | 17500 | 1.9206          |
| 1.7177        | 24.83 | 18000 | 1.9125          |
| 1.7117        | 25.52 | 18500 | 1.9178          |
| 1.6834        | 26.21 | 19000 | 1.9082          |
| 1.6893        | 26.9  | 19500 | 1.9124          |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0.dev20211231+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1