---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
- accuracy
model-index:
- name: trocr-small-printedkorean-deleteunusedchar
  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. -->

# trocr-small-printedkorean-deleteunusedchar

This model is a fine-tuned version of [team-lucid/trocr-small-korean](https://huggingface.co/team-lucid/trocr-small-korean) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1253
- Cer: 0.3884
- Wer: 0.4405
- Accuracy: 27.0903

## 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: 4e-05
- train_batch_size: 128
- eval_batch_size: 192
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Cer    | Wer    | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|
| 3.5404        | 0.43  | 1000  | 3.5688          | 0.5737 | 0.6446 | 17.7258  |
| 3.365         | 0.85  | 2000  | 3.4212          | 0.5664 | 0.6546 | 18.0602  |
| 3.266         | 1.28  | 3000  | 3.3538          | 0.5637 | 0.6815 | 18.7291  |
| 3.2922        | 1.71  | 4000  | 3.3051          | 0.5613 | 0.7161 | 18.0602  |
| 3.1287        | 2.13  | 5000  | 3.2649          | 0.5577 | 0.7164 | 18.7291  |
| 3.0906        | 2.56  | 6000  | 3.2016          | 0.5572 | 0.6139 | 18.3946  |
| 3.0015        | 2.99  | 7000  | 3.0851          | 0.5530 | 0.6018 | 18.3946  |
| 2.7418        | 3.42  | 8000  | 2.8927          | 0.5264 | 0.6052 | 19.3980  |
| 2.5107        | 3.84  | 9000  | 2.6466          | 0.4821 | 0.5881 | 19.3980  |
| 2.3091        | 4.27  | 10000 | 2.4865          | 0.4545 | 0.5651 | 20.4013  |
| 2.1395        | 4.7   | 11000 | 2.3749          | 0.4336 | 0.5323 | 21.7391  |
| 2.0453        | 5.12  | 12000 | 2.3070          | 0.4222 | 0.5157 | 21.7391  |
| 2.0421        | 5.55  | 13000 | 2.2667          | 0.4143 | 0.5001 | 24.0803  |
| 2.0085        | 5.98  | 14000 | 2.2201          | 0.4060 | 0.4809 | 24.0803  |
| 1.8766        | 6.4   | 15000 | 2.1988          | 0.4026 | 0.4766 | 23.7458  |
| 1.8987        | 6.83  | 16000 | 2.1788          | 0.3969 | 0.4658 | 24.4147  |
| 1.8921        | 7.26  | 17000 | 2.1702          | 0.3955 | 0.4581 | 24.4147  |
| 1.8253        | 7.69  | 18000 | 2.1554          | 0.3938 | 0.4513 | 26.7559  |
| 1.8281        | 8.11  | 19000 | 2.1481          | 0.3925 | 0.4534 | 26.0870  |
| 1.8751        | 8.54  | 20000 | 2.1419          | 0.3905 | 0.4500 | 26.0870  |
| 1.8226        | 8.97  | 21000 | 2.1317          | 0.3905 | 0.4439 | 26.7559  |
| 1.813         | 9.39  | 22000 | 2.1285          | 0.3895 | 0.4407 | 26.0870  |
| 1.7472        | 9.82  | 23000 | 2.1253          | 0.3884 | 0.4405 | 27.0903  |


### Framework versions

- Transformers 4.28.0
- Pytorch 1.13.1+cu116
- Datasets 2.14.4
- Tokenizers 0.13.3