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donut-base-sroie – AI Model by JoaoRaimundo | AlphaNeural AI
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donut-base-sroie
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transformers
tensorboard
safetensors
vision-encoder-decoder
image-to-text
generated_from_trainer
imagefolder
naver-clova-ix/donut-base
finetune
mit
endpoints_compatible
us
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donut-base-sroie
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: 3e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Use 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: 10
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.55.0
Pytorch 2.8.0+cu128
Datasets 4.0.0
Tokenizers 0.21.4
