transformers tensorboard safetensors vision-encoder-decoder image-text-to-text generated_from_trainer base_model:naver-clova-ix/donut-base base_model:finetune:naver-clova-ix/donut-base license:mit endpoints_compatible region:us
---
base_model: naver-clova-ix/donut-base
license: mit
metrics:
- bleu
- wer
tags:
- generated_from_trainer
model-index:
- name: donut_experiment_bayesian_trial_5
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# donut_experiment_bayesian_trial_5

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: 0.4541
- Bleu: 0.0661
- Precisions: [0.8029045643153527, 0.731764705882353, 0.6875, 0.639871382636656]
- Brevity Penalty: 0.0928
- Length Ratio: 0.2961
- Translation Length: 482
- Reference Length: 1628
- Cer: 0.7590
- Wer: 0.8315

## 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: 0.00018010138886762352
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|
| 0.655         | 1.0   | 253  | 0.5770          | 0.0681 | [0.7555110220440882, 0.6719457013574661, 0.625974025974026, 0.5762195121951219] | 0.1041          | 0.3065       | 499                | 1628             | 0.7627 | 0.8438 |
| 0.183         | 2.0   | 506  | 0.4541          | 0.0661 | [0.8029045643153527, 0.731764705882353, 0.6875, 0.639871382636656]              | 0.0928          | 0.2961       | 482                | 1628             | 0.7590 | 0.8315 |


### Framework versions

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