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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: 0.4747

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: 4
• total_train_batch_size: 4
• 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
• lr_scheduler_warmup_steps: 100
• num_epochs: 15
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
12.9586	1.0754	200	2.1653
4.3160	2.1507	400	1.0573
2.1071	3.2261	600	0.6039
0.9479	4.3015	800	0.4992
0.6713	5.3769	1000	0.4486
0.6128	6.4522	1200	0.4649
0.5284	7.5276	1400	0.4505
0.3932	8.6030	1600	0.4747

Framework versions

• Transformers 5.10.2
• Pytorch 2.11.0+cu128
• Datasets 4.0.0
• Tokenizers 0.22.2