donut-base-my_model_rapido_2_new_check_2

Manab/donut-base-my_model_rapido_2_new_check_2

donut-base-my_model_rapido_2_new_check_2 is a image-text-to-text model from Manab. 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. --

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At a glance

Task: Image-Text-to-Text
Library: transformers
License: mit
Model type: vision-encoder-decoder
Access: Public
Created: Jul 7, 2023
Updated: Jul 7, 2023
SHA: 18a2a3e3

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Base models

naver-clova-ix/donut-base

Datasets

imagefolder

Model card

From the Hugging Face model README

donut-base-my_model_rapido_2_new_check_2

This model is a fine-tuned version of naver-clova-ix/donut-base on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 2.8819

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: 1e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
9.9118	0.69	50	6.5666
6.0851	1.39	100	4.2864
4.4899	2.08	150	3.3172
3.6628	2.78	200	2.8819

Framework versions

Transformers 4.31.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

Task: Image-Text-to-Text
Library: transformers
Type: vision-encoder-decoder
License: mit
Created: Jul 7, 2023
Updated: Jul 7, 2023