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donut_payslip_LeMa – AI Model by konstantis | AlphaNeural AI
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konstantis
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donut_payslip_LeMa
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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_payslip_LeMa
This model is a fine-tuned version of
naver-clova-ix/donut-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5993
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: 8
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: 12
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.965
1.0
1000
0.9175
0.5617
2.0
2000
0.6567
0.3202
3.0
3000
0.5667
0.1697
4.0
4000
0.6694
0.097
5.0
5000
0.5993
Framework versions
Transformers 4.53.0.dev0
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.1
