transformers pytorch vision-encoder-decoder generated_from_trainer dataset:imagefolder base_model:naver-clova-ix/donut-base license:mit endpoints_compatible region:us
---
license: mit
base_model: naver-clova-ix/donut-base
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: donut-base2-sroie
  results: []
---

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# donut-base2-sroie

This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3234

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.1171        | 1.0   | 73   | 3.5216          |
| 2.6172        | 2.0   | 146  | 1.8420          |
| 2.1784        | 3.0   | 219  | 1.3622          |
| 1.0188        | 4.0   | 292  | 1.2344          |
| 0.8844        | 5.0   | 365  | 1.2448          |
| 0.4622        | 6.0   | 438  | 1.1840          |
| 0.8648        | 7.0   | 511  | 1.2136          |
| 0.4117        | 8.0   | 584  | 1.2452          |
| 0.2687        | 9.0   | 657  | 1.2622          |
| 0.4633        | 10.0  | 730  | 1.2959          |
| 0.4606        | 11.0  | 803  | 1.3234          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
