donut-base-keyadded

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: 0.2338

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: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss
1.2872	1.0	141	1.2093
0.791	2.0	282	0.6119
0.3808	3.0	423	0.4572
0.6405	4.0	564	0.3678
0.5345	5.0	705	0.3261
0.0957	6.0	846	0.2967
0.2616	7.0	987	0.2722
0.0842	8.0	1128	0.2622
0.0524	9.0	1269	0.2507
0.0905	10.0	1410	0.2458
0.1562	11.0	1551	0.2369
0.0478	12.0	1692	0.2338

Framework versions

• Transformers 4.34.1
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1