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donut-base-full_text_wt_val_1008

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metadata
license: mit
base_model: naver-clova-ix/donut-base
tags:
  - generated_from_trainer
datasets:
  - imagefolder
model-index:
  - name: donut-base-full_text_wt_val_1008
    results: []

donut-base-full_text_wt_val_1008

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: 0.1060

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: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
1.9227 0.2 100 0.6985
0.6852 0.4 200 0.4421
0.5102 0.6 300 0.3346
0.4178 0.79 400 0.2886
0.4476 0.99 500 0.2455
0.2931 1.19 600 0.2287
0.2647 1.39 700 0.2072
0.2418 1.59 800 0.1905
0.3031 1.79 900 0.1754
0.2306 1.98 1000 0.1667
0.2031 2.18 1100 0.1619
0.1918 2.38 1200 0.1536
0.1802 2.58 1300 0.1504
0.1646 2.78 1400 0.1436
0.1816 2.98 1500 0.1379
0.1344 3.17 1600 0.1395
0.1752 3.37 1700 0.1336
0.1388 3.57 1800 0.1306
0.1402 3.77 1900 0.1262
0.1123 3.97 2000 0.1277
0.144 4.17 2100 0.1248
0.1077 4.37 2200 0.1226
0.1134 4.56 2300 0.1186
0.1192 4.76 2400 0.1179
0.1142 4.96 2500 0.1194
0.1426 5.16 2600 0.1202
0.1022 5.36 2700 0.1165
0.0815 5.56 2800 0.1164
0.1096 5.75 2900 0.1166
0.0866 5.95 3000 0.1121
0.1148 6.15 3100 0.1122
0.0771 6.35 3200 0.1129
0.0996 6.55 3300 0.1096
0.0622 6.75 3400 0.1099
0.0985 6.94 3500 0.1092
0.0684 7.14 3600 0.1097
0.0669 7.34 3700 0.1086
0.0624 7.54 3800 0.1088
0.0763 7.74 3900 0.1069
0.0579 7.94 4000 0.1060
0.0623 8.13 4100 0.1083
0.0599 8.33 4200 0.1058
0.0625 8.53 4300 0.1073
0.0499 8.73 4400 0.1059
0.0628 8.93 4500 0.1059
0.0684 9.13 4600 0.1063
0.0472 9.33 4700 0.1056
0.068 9.52 4800 0.1057
0.06 9.72 4900 0.1062
0.0636 9.92 5000 0.1060

Framework versions

  • Transformers 4.38.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1