---
license: mit
base_model: naver-clova-ix/donut-base
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: donut_sm_type1_04-12-23
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# donut_sm_type1_04-12-23

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: 0.1251

## 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5232        | 1.0   | 200  | 0.2651          |
| 0.3372        | 2.0   | 400  | 0.1358          |
| 0.0603        | 3.0   | 600  | 0.1150          |
| 0.0727        | 4.0   | 800  | 0.1130          |
| 0.0231        | 5.0   | 1000 | 0.1195          |
| 0.0318        | 6.0   | 1200 | 0.1229          |
| 0.0118        | 7.0   | 1400 | 0.1243          |
| 0.0153        | 8.0   | 1600 | 0.1469          |
| 0.0152        | 9.0   | 1800 | 0.1251          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0