donut-classification-turbo

hf-tuner/donut-classification-turbo

donut-classification-turbo is a image-text-to-text model from hf-tuner. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

16% of all-time downloads

All-time downloads

Public

Parameters

201M

804 MB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors803 MB · 99%

Parameter types

How the weights are stored.

F32200M · 100%

Try a prompt

Base models

hf-tuner/donut-efficient-test2

Datasets

hf-tuner/rvl-cdip-document-classification

Model card

From the Hugging Face model README

donut-classification-turbo

This model is a fine-tuned version of donut-base-finetuned-rvl-cdip on rvl-cdip-document-classification dataset. It achieves the following results on the evaluation set:

Loss: 0.0499
Accuracy: 93.34%

confusion matrix

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 2
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.1319	0.5	2000	0.1200
0.1365	1.0	4000	0.0845
0.1203	1.5	6000	0.0751
0.1128	2.0	8000	0.0677
0.0734	2.5	10000	0.0541
0.0707	3.0	12000	0.0499

Framework versions

Transformers 4.56.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1

Task: Image-Text-to-Text
Library: transformers
Type: vision-encoder-decoder
License: mit
Languages: en, ko, ja, zh
Created: Oct 14, 2025
Updated: Oct 15, 2025