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donut-inverter-finetuned – AI Model by adikuma | AlphaNeural AI
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adikuma
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donut-inverter-finetuned
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transformers
safetensors
vision-encoder-decoder
image-text-to-text
generated_from_trainer
naver-clova-ix/donut-base
finetune
mit
endpoints_compatible
us
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donut-inverter-finetuned
This model is a fine-tuned version of
naver-clova-ix/donut-base
on an unknown 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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
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: 5
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.57.2
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
