---
license: mit
base_model: naver-clova-ix/donut-base
tags:
- generated_from_trainer
metrics:
- bleu
- wer
model-index:
- name: donut_experiment_bayesian_trial_9
  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_9

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: 0.5922
- Bleu: 0.0587
- Precisions: [0.735655737704918, 0.6310904872389791, 0.5668449197860963, 0.5173501577287066]
- Brevity Penalty: 0.0967
- Length Ratio: 0.2998
- Translation Length: 488
- Reference Length: 1628
- Cer: 0.7688
- Wer: 0.8559

## 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: 1.393489197537874e-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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|
| 1.1982        | 1.0   | 253  | 0.7300          | 0.0555 | [0.6828282828282828, 0.5616438356164384, 0.5091863517060368, 0.45987654320987653] | 0.1014          | 0.3041       | 495                | 1628             | 0.7812 | 0.8659 |
| 0.5755        | 2.0   | 506  | 0.5922          | 0.0587 | [0.735655737704918, 0.6310904872389791, 0.5668449197860963, 0.5173501577287066]   | 0.0967          | 0.2998       | 488                | 1628             | 0.7688 | 0.8559 |


### Framework versions

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