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donut-base-finetuned-docvqa-1200-v2 – AI Model by sam749 | AlphaNeural AI
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donut-base-finetuned-docvqa-1200-v2
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transformers
tensorboard
safetensors
vision-encoder-decoder
image-to-text
generated_from_trainer
naver-clova-ix/donut-base
finetune
mit
endpoints_compatible
us
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donut-base-finetuned-docvqa-1200-v2
This model is a fine-tuned version of
naver-clova-ix/donut-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 2.7487
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
optimizer: Use OptimizerNames.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
2.2259
1.0
1000
2.7825
1.61
2.0
2000
2.7137
1.3079
3.0
3000
2.7487
Framework versions
Transformers 4.48.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0
