---
license: mit
base_model: naver-clova-ix/donut-proto
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: donut-proto-sroie
  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-proto-sroie

This model is a fine-tuned version of [naver-clova-ix/donut-proto](https://huggingface.co/naver-clova-ix/donut-proto) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9048

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 7.7533        | 1.0   | 73   | 7.3383          |
| 6.2747        | 2.0   | 146  | 5.8340          |
| 4.5766        | 3.0   | 219  | 4.4653          |
| 4.2866        | 4.0   | 292  | 3.6184          |
| 3.5846        | 5.0   | 365  | 3.3728          |
| 3.5065        | 6.0   | 438  | 3.2303          |
| 2.8412        | 7.0   | 511  | 3.1083          |
| 3.4091        | 8.0   | 584  | 3.0442          |
| 3.0191        | 9.0   | 657  | 3.0130          |
| 2.5351        | 10.0  | 730  | 2.9678          |
| 2.9271        | 11.0  | 803  | 2.9627          |
| 2.7935        | 12.0  | 876  | 2.9427          |
| 3.0205        | 13.0  | 949  | 2.9298          |
| 3.1783        | 14.0  | 1022 | 2.9204          |
| 3.0527        | 15.0  | 1095 | 2.9210          |
| 2.2231        | 16.0  | 1168 | 2.9251          |
| 2.1284        | 17.0  | 1241 | 2.9015          |
| 2.6874        | 18.0  | 1314 | 2.9099          |
| 2.5325        | 19.0  | 1387 | 2.9091          |
| 2.6132        | 20.0  | 1460 | 2.9048          |


### Framework versions

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