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donut_experiment_bayesian_trial_20

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: 0.6042
  • Bleu: 0.0711
  • Precisions: [0.8440748440748441, 0.7924528301886793, 0.7493188010899182, 0.7064516129032258]
  • Brevity Penalty: 0.0921
  • Length Ratio: 0.2955
  • Translation Length: 481
  • Reference Length: 1628
  • Cer: 0.7518
  • Wer: 0.8208

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: 1.4151037707088747e-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
0.0012 1.0 253 0.6392 0.0724 [0.8333333333333334, 0.7762237762237763, 0.7365591397849462, 0.6952380952380952] 0.0954 0.2985 486 1628 0.7482 0.8193
0.0068 2.0 506 0.6212 0.0697 [0.8413361169102297, 0.7867298578199052, 0.7452054794520548, 0.7012987012987013] 0.0908 0.2942 479 1628 0.7527 0.8230
0.0087 3.0 759 0.6105 0.0687 [0.83125, 0.7706855791962175, 0.726775956284153, 0.6828478964401294] 0.0915 0.2948 480 1628 0.7573 0.8282
0.0056 4.0 1012 0.6042 0.0711 [0.8440748440748441, 0.7924528301886793, 0.7493188010899182, 0.7064516129032258] 0.0921 0.2955 481 1628 0.7518 0.8208

Framework versions

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