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donut-base-contigo – AI Model by DalHyun | AlphaNeural AI

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DalHyun/
donut-base-contigo

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vision-encoder-decoder

generated_from_trainer

naver-clova-ix/donut-base

endpoints_compatible

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donut-base-contigo

This model is a fine-tuned version of naver-clova-ix/donut-base on the imagefolder dataset.

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: 4
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50
mixed_precision_training: Native AMP

Training results

Framework versions

Transformers 4.41.0.dev0
Pytorch 2.3.0+cu121
Datasets 2.12.0
Tokenizers 0.19.1