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---
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: 0.4671
- Bleu: 0.0662
- Precisions: [0.785140562248996, 0.6825396825396826, 0.6197916666666666, 0.5626911314984709]
- Brevity Penalty: 0.1007
- Length Ratio: 0.3035
- Translation Length: 498
- Reference Length: 1641
- Cer: 0.7528
- Wer: 0.8385
## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:----------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|
| 3.6559 | 1.0 | 253 | 1.5613 | 0.0007 | [0.5056179775280899, 0.1943127962085308, 0.07692307692307693, 0.02830188679245283] | 0.0058 | 0.1627 | 267 | 1641 | 0.8768 | 0.9436 |
| 1.2493 | 2.0 | 506 | 0.6697 | 0.0409 | [0.6560509554140127, 0.5048309178743962, 0.4481792717086835, 0.39] | 0.0834 | 0.2870 | 471 | 1641 | 0.7766 | 0.8837 |
| 0.9257 | 3.0 | 759 | 0.5168 | 0.0594 | [0.75, 0.6275862068965518, 0.5714285714285714, 0.5264797507788161] | 0.0968 | 0.2998 | 492 | 1641 | 0.7570 | 0.8499 |
| 0.6416 | 4.0 | 1012 | 0.4671 | 0.0662 | [0.785140562248996, 0.6825396825396826, 0.6197916666666666, 0.5626911314984709] | 0.1007 | 0.3035 | 498 | 1641 | 0.7528 | 0.8385 |
### Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.1.0
- Datasets 2.19.1
- Tokenizers 0.19.1
|