---
license: mit
base_model: naver-clova-ix/donut-base
tags:
- generated_from_trainer
metrics:
- bleu
- wer
model-index:
- name: donut_experiment_bayesian_trial_13
  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_13

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: 0.5500
- Bleu: 0.0682
- Precisions: [0.8219461697722568, 0.755868544600939, 0.7073170731707317, 0.6474358974358975]
- Brevity Penalty: 0.0934
- Length Ratio: 0.2967
- Translation Length: 483
- Reference Length: 1628
- Cer: 0.7531
- Wer: 0.8285

## 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: 6.0814226870239416e-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: 2
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|
| 0.0455        | 1.0   | 253  | 0.5262          | 0.0660 | [0.8166666666666667, 0.7446808510638298, 0.6939890710382514, 0.6407766990291263] | 0.0915          | 0.2948       | 480                | 1628             | 0.7601 | 0.8316 |
| 0.0276        | 2.0   | 506  | 0.5500          | 0.0682 | [0.8219461697722568, 0.755868544600939, 0.7073170731707317, 0.6474358974358975]  | 0.0934          | 0.2967       | 483                | 1628             | 0.7531 | 0.8285 |


### Framework versions

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