donut-base-sroie-test-050824

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: 0.5823
• Bleu: 0.0595
• Precisions: [0.7332123411978222, 0.6290983606557377, 0.5741176470588235, 0.5248618784530387]
• Brevity Penalty: 0.0974
• Length Ratio: 0.3004
• Translation Length: 551
• Reference Length: 1834
• Cer: 0.7739
• Wer: 0.8665

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: 2
• total_train_batch_size: 2
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Precisions	Brevity Penalty	Length Ratio	Translation Length	Reference Length	Cer	Wer
3.716	1.0	250	1.7346	0.0080	[0.3276089828269485, 0.05475504322766571, 0.01901743264659271, 0.0035211267605633804]	0.2411	0.4128	757	1834	0.8647	0.9639
1.3396	2.0	500	0.8150	0.0346	[0.6405353728489483, 0.46304347826086956, 0.3702770780856423, 0.2964071856287425]	0.0815	0.2852	523	1834	0.7877	0.8990
0.8804	3.0	750	0.6424	0.0586	[0.7463235294117647, 0.6486486486486487, 0.5933014354066986, 0.5408450704225352]	0.0934	0.2966	544	1834	0.7674	0.8638
0.6436	4.0	1000	0.5823	0.0595	[0.7332123411978222, 0.6290983606557377, 0.5741176470588235, 0.5248618784530387]	0.0974	0.3004	551	1834	0.7739	0.8665

Framework versions

• Transformers 4.41.0.dev0
• Pytorch 2.1.0
• Datasets 2.19.1
• Tokenizers 0.19.1