---
base_model: klue/roberta-small
tags:
- generated_from_trainer
model-index:
- name: my_model
  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. -->

# my_model

This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4546

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 1.5259        | 1.0   | 4820   | 1.3120          |
| 1.2116        | 2.0   | 9640   | 1.0790          |
| 1.0629        | 3.0   | 14460  | 0.9467          |
| 0.9722        | 4.0   | 19280  | 0.8650          |
| 0.912         | 5.0   | 24100  | 0.8258          |
| 0.8514        | 6.0   | 28920  | 0.7731          |
| 0.8308        | 7.0   | 33740  | 0.7558          |
| 0.7854        | 8.0   | 38560  | 0.7081          |
| 0.74          | 9.0   | 43380  | 0.6947          |
| 0.738         | 10.0  | 48200  | 0.6608          |
| 0.7335        | 11.0  | 53020  | 0.6485          |
| 0.675         | 12.0  | 57840  | 0.6354          |
| 0.6655        | 13.0  | 62660  | 0.6106          |
| 0.6458        | 14.0  | 67480  | 0.6029          |
| 0.6256        | 15.0  | 72300  | 0.5821          |
| 0.6191        | 16.0  | 77120  | 0.5737          |
| 0.5979        | 17.0  | 81940  | 0.5696          |
| 0.6           | 18.0  | 86760  | 0.5595          |
| 0.5812        | 19.0  | 91580  | 0.5317          |
| 0.5736        | 20.0  | 96400  | 0.5282          |
| 0.5597        | 21.0  | 101220 | 0.5407          |
| 0.5665        | 22.0  | 106040 | 0.5404          |
| 0.5546        | 23.0  | 110860 | 0.5320          |
| 0.5574        | 24.0  | 115680 | 0.5160          |
| 0.5346        | 25.0  | 120500 | 0.5220          |
| 0.5323        | 26.0  | 125320 | 0.5099          |
| 0.5251        | 27.0  | 130140 | 0.4943          |
| 0.5254        | 28.0  | 134960 | 0.4907          |
| 0.5154        | 29.0  | 139780 | 0.4761          |
| 0.4914        | 30.0  | 144600 | 0.4958          |
| 0.5085        | 31.0  | 149420 | 0.4595          |
| 0.4897        | 32.0  | 154240 | 0.4697          |
| 0.4868        | 33.0  | 159060 | 0.4664          |
| 0.4779        | 34.0  | 163880 | 0.4684          |
| 0.4732        | 35.0  | 168700 | 0.4781          |
| 0.4757        | 36.0  | 173520 | 0.4687          |
| 0.4702        | 37.0  | 178340 | 0.4484          |
| 0.4652        | 38.0  | 183160 | 0.4522          |
| 0.4522        | 39.0  | 187980 | 0.4622          |
| 0.4559        | 40.0  | 192800 | 0.4546          |
| 0.4558        | 41.0  | 197620 | 0.4370          |
| 0.4482        | 42.0  | 202440 | 0.4359          |
| 0.4451        | 43.0  | 207260 | 0.4467          |
| 0.4383        | 44.0  | 212080 | 0.4401          |
| 0.4489        | 45.0  | 216900 | 0.4309          |
| 0.4347        | 46.0  | 221720 | 0.4256          |
| 0.4356        | 47.0  | 226540 | 0.4423          |
| 0.4447        | 48.0  | 231360 | 0.4441          |
| 0.4324        | 49.0  | 236180 | 0.4405          |
| 0.4278        | 50.0  | 241000 | 0.4306          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0