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---
license: mit
base_model: naver-clova-ix/donut-base
tags:
- generated_from_trainer
metrics:
- bleu
- wer
model-index:
- name: donut_experiment_2
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_2
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: 0.3855
- Bleu: 0.0663
- Precisions: [0.8273684210526315, 0.7703349282296651, 0.7285318559556787, 0.6842105263157895]
- Brevity Penalty: 0.0883
- Length Ratio: 0.2918
- Translation Length: 475
- Reference Length: 1628
- Cer: 0.7539
- Wer: 0.8251
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|
| 0.9517 | 1.0 | 253 | 0.5797 | 0.0543 | [0.7160751565762005, 0.6184834123222749, 0.5671232876712329, 0.5097402597402597] | 0.0908 | 0.2942 | 479 | 1628 | 0.7738 | 0.8500 |
| 0.3907 | 2.0 | 506 | 0.4532 | 0.0590 | [0.7851063829787234, 0.711864406779661, 0.6657303370786517, 0.6220735785953178] | 0.0851 | 0.2887 | 470 | 1628 | 0.7610 | 0.8370 |
| 0.3245 | 3.0 | 759 | 0.4102 | 0.0625 | [0.8008474576271186, 0.7397590361445783, 0.7011173184357542, 0.6611295681063123] | 0.0864 | 0.2899 | 472 | 1628 | 0.7593 | 0.8336 |
| 0.2318 | 4.0 | 1012 | 0.3855 | 0.0663 | [0.8273684210526315, 0.7703349282296651, 0.7285318559556787, 0.6842105263157895] | 0.0883 | 0.2918 | 475 | 1628 | 0.7539 | 0.8251 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.1.0
- Datasets 2.18.0
- Tokenizers 0.19.1
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