davelotito/donut-base-sroie-metrics-combined

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donut-base-sroie-metrics-combined

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: 0.2827
• —Bleu score: 0.0762
• —Precisions: [0.8396396396396396, 0.7886178861788617, 0.7435897435897436, 0.7049180327868853]
• —Brevity penalty: 0.0993
• —Length ratio: 0.3021
• —Translation length: 555
• —Reference length: 1837
• —Cer: 0.7452
• —Wer: 0.8162
• —Cer Hugging Face: 0.7544
• —Wer Hugging Face: 0.8233

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
• —trainbatchsize: 4
• —evalbatchsize: 4
• —seed: 42
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 8
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 4
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.40.0.dev0
• —Pytorch 2.1.0
• —Datasets 2.18.0
• —Tokenizers 0.15.2