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donut-finetuned – AI Model by Ronysalem | AlphaNeural AI
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Ronysalem
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donut-finetuned
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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-finetuned
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: 4.1680
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: 2
eval_batch_size: 2
seed: 42
optimizer: Use adamw_torch 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
No log
1.0
3
5.0771
No log
2.0
6
4.4206
No log
3.0
9
4.1680
Framework versions
Transformers 4.50.0.dev0
Pytorch 2.5.1+cpu
Datasets 3.2.0
Tokenizers 0.21.0
