---
license: mit
base_model: naver-clova-ix/donut-base
tags:
- generated_from_trainer
metrics:
- bleu
- wer
model-index:
- name: donut_experiment_bayesian_trial_12
  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_12

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: 0.5083
- Bleu: 0.0675
- Precisions: [0.8421052631578947, 0.7822966507177034, 0.7423822714681441, 0.7006578947368421]
- Brevity Penalty: 0.0883
- Length Ratio: 0.2918
- Translation Length: 475
- Reference Length: 1628
- Cer: 0.7537
- Wer: 0.8211

## 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: 1.2643161326759464e-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: 3
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|
| 0.0251        | 1.0   | 253  | 0.4936          | 0.0660 | [0.8375527426160337, 0.7673860911270983, 0.7277777777777777, 0.6897689768976898] | 0.0876          | 0.2912       | 474                | 1628             | 0.7600 | 0.8274 |
| 0.0144        | 2.0   | 506  | 0.4987          | 0.0683 | [0.8445378151260504, 0.7852028639618138, 0.7458563535911602, 0.7049180327868853] | 0.0889          | 0.2924       | 476                | 1628             | 0.7515 | 0.8189 |
| 0.0089        | 3.0   | 759  | 0.5083          | 0.0675 | [0.8421052631578947, 0.7822966507177034, 0.7423822714681441, 0.7006578947368421] | 0.0883          | 0.2918       | 475                | 1628             | 0.7537 | 0.8211 |


### Framework versions

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