---
license: mit
base_model: naver-clova-ix/donut-base
tags:
- generated_from_trainer
metrics:
- bleu
- wer
model-index:
- name: donut-base-sroie-metrics-combined-new
  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-base-sroie-metrics-combined-new

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: 0.3171
- Bleu: 0.0705
- Precisions: [0.8333333333333334, 0.7599067599067599, 0.7123655913978495, 0.6761904761904762]
- Brevity Penalty: 0.0948
- Length Ratio: 0.2980
- Translation Length: 486
- Reference Length: 1631
- Cer: 0.7492
- Wer: 0.8169

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
- 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:---------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|
| 6.4453        | 0.9960  | 126  | 2.4195          | 0.0    | [0.4214046822742475, 0.08130081300813008, 0.02040816326530612, 0.0]               | 0.0116          | 0.1833       | 299                | 1631             | 0.9070 | 0.9677 |
| 2.7428        | 2.0     | 253  | 1.0515          | 0.0210 | [0.6041666666666666, 0.3696808510638298, 0.2772585669781931, 0.20676691729323307] | 0.0623          | 0.2649       | 432                | 1631             | 0.8040 | 0.9235 |
| 1.5566        | 2.9960  | 379  | 0.6386          | 0.0442 | [0.7029914529914529, 0.5693430656934306, 0.480225988700565, 0.4107744107744108]   | 0.0833          | 0.2869       | 468                | 1631             | 0.7640 | 0.8789 |
| 0.8362        | 4.0     | 506  | 0.4649          | 0.0646 | [0.7570281124497992, 0.6485260770975056, 0.5911458333333334, 0.5382262996941896]  | 0.1028          | 0.3053       | 498                | 1631             | 0.7585 | 0.8472 |
| 0.6682        | 4.9960  | 632  | 0.4224          | 0.0636 | [0.7540322580645161, 0.6514806378132119, 0.5916230366492147, 0.5323076923076923]  | 0.1014          | 0.3041       | 496                | 1631             | 0.7607 | 0.8464 |
| 0.5031        | 6.0     | 759  | 0.3836          | 0.0655 | [0.7857142857142857, 0.6928406466512702, 0.6382978723404256, 0.5893416927899686]  | 0.0974          | 0.3004       | 490                | 1631             | 0.7561 | 0.8344 |
| 0.446         | 6.9960  | 885  | 0.3603          | 0.0694 | [0.8179959100204499, 0.7384259259259259, 0.6853333333333333, 0.6383647798742138]  | 0.0968          | 0.2998       | 489                | 1631             | 0.7526 | 0.8313 |
| 0.3507        | 8.0     | 1012 | 0.3284          | 0.0700 | [0.8118609406952966, 0.7407407407407407, 0.696, 0.6540880503144654]               | 0.0968          | 0.2998       | 489                | 1631             | 0.7534 | 0.8262 |
| 0.2981        | 8.9960  | 1138 | 0.3234          | 0.0687 | [0.8340248962655602, 0.7623529411764706, 0.720108695652174, 0.6752411575562701]   | 0.0922          | 0.2955       | 482                | 1631             | 0.7488 | 0.8198 |
| 0.322         | 10.0    | 1265 | 0.3247          | 0.0705 | [0.8295687885010267, 0.7511627906976744, 0.710455764075067, 0.6708860759493671]   | 0.0955          | 0.2986       | 487                | 1631             | 0.7518 | 0.8219 |
| 0.2581        | 10.9960 | 1391 | 0.3154          | 0.0704 | [0.8429752066115702, 0.7681498829039812, 0.7243243243243244, 0.6869009584664537]  | 0.0935          | 0.2968       | 484                | 1631             | 0.7485 | 0.8162 |
| 0.2311        | 11.9526 | 1512 | 0.3171          | 0.0705 | [0.8333333333333334, 0.7599067599067599, 0.7123655913978495, 0.6761904761904762]  | 0.0948          | 0.2980       | 486                | 1631             | 0.7492 | 0.8169 |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.1.0
- Datasets 2.19.1
- Tokenizers 0.19.1