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metadata
license: mit
base_model: naver-clova-ix/donut-base
tags:
  - generated_from_trainer
metrics:
  - bleu
  - wer
model-index:
  - name: donut_experiment_bayesian_trial_16
    results: []

donut_experiment_bayesian_trial_16

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: 0.5541
  • Bleu: 0.0670
  • Precisions: [0.8417721518987342, 0.7841726618705036, 0.7388888888888889, 0.6996699669966997]
  • Brevity Penalty: 0.0876
  • Length Ratio: 0.2912
  • Translation Length: 474
  • Reference Length: 1628
  • Cer: 0.7567
  • Wer: 0.8224

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: 0.00011219603369833024
  • 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
0.0965 1.0 253 0.5550 0.0624 [0.7995824634655533, 0.7085308056872038, 0.6520547945205479, 0.6038961038961039] 0.0908 0.2942 479 1628 0.7576 0.8347
0.0844 2.0 506 0.5896 0.0651 [0.8218029350104822, 0.7476190476190476, 0.696969696969697, 0.6535947712418301] 0.0895 0.2930 477 1628 0.7557 0.8302
0.0539 3.0 759 0.5594 0.0666 [0.8322851153039832, 0.7642857142857142, 0.7134986225895317, 0.673202614379085] 0.0895 0.2930 477 1628 0.7552 0.8223
0.023 4.0 1012 0.5541 0.0670 [0.8417721518987342, 0.7841726618705036, 0.7388888888888889, 0.6996699669966997] 0.0876 0.2912 474 1628 0.7567 0.8224

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.1.0
  • Datasets 2.18.0
  • Tokenizers 0.19.1