---
license: mit
base_model: naver-clova-ix/donut-base
tags:
- generated_from_trainer
metrics:
- bleu
- wer
model-index:
- name: donut_experiment_bayesian_trial_20
  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. -->

# donut_experiment_bayesian_trial_20

This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6042
- Bleu: 0.0711
- Precisions: [0.8440748440748441, 0.7924528301886793, 0.7493188010899182, 0.7064516129032258]
- Brevity Penalty: 0.0921
- Length Ratio: 0.2955
- Translation Length: 481
- Reference Length: 1628
- Cer: 0.7518
- Wer: 0.8208

## 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: 1.4151037707088747e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Precisions                                                                       | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Cer    | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|
| 0.0012        | 1.0   | 253  | 0.6392          | 0.0724 | [0.8333333333333334, 0.7762237762237763, 0.7365591397849462, 0.6952380952380952] | 0.0954          | 0.2985       | 486                | 1628             | 0.7482 | 0.8193 |
| 0.0068        | 2.0   | 506  | 0.6212          | 0.0697 | [0.8413361169102297, 0.7867298578199052, 0.7452054794520548, 0.7012987012987013] | 0.0908          | 0.2942       | 479                | 1628             | 0.7527 | 0.8230 |
| 0.0087        | 3.0   | 759  | 0.6105          | 0.0687 | [0.83125, 0.7706855791962175, 0.726775956284153, 0.6828478964401294]             | 0.0915          | 0.2948       | 480                | 1628             | 0.7573 | 0.8282 |
| 0.0056        | 4.0   | 1012 | 0.6042          | 0.0711 | [0.8440748440748441, 0.7924528301886793, 0.7493188010899182, 0.7064516129032258] | 0.0921          | 0.2955       | 481                | 1628             | 0.7518 | 0.8208 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.1.0
- Datasets 2.18.0
- Tokenizers 0.19.1