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InvoiceDonut1-5Epochs-LargeTrain1 – AI Model by tedad09 | AlphaNeural AI
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InvoiceDonut1-5Epochs-LargeTrain1
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tensorboard
safetensors
vision-encoder-decoder
generated_from_trainer
imagefolder
naver-clova-ix/donut-base
finetune
mit
us
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InvoiceDonut1-5Epochs-LargeTrain1
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: 0.0959
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
1.294
1.0
207
0.1126
0.1678
2.0
414
0.1248
0.122
3.0
621
0.0887
0.083
4.0
828
0.0872
0.055
5.0
1035
0.0959
Framework versions
Transformers 4.38.2
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.15.2
