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IS557_TrOCR_AllData

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metadata
base_model: microsoft/trocr-base-stage1
tags:
  - generated_from_trainer
model-index:
  - name: IS557_TrOCR_AllData
    results: []

IS557_TrOCR_AllData

This model is a fine-tuned version of microsoft/trocr-base-stage1 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0124
  • Cer: 0.1764

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer
4.4421 0.0708 200 4.1713 0.6172
3.2966 0.1415 400 3.1228 0.5064
2.5955 0.2123 600 2.7626 0.3949
2.201 0.2831 800 2.4729 0.4258
1.5876 0.3539 1000 2.2295 0.3097
2.7774 0.4246 1200 2.1112 0.3092
2.7995 0.4954 1400 2.1286 0.3070
1.5241 0.5662 1600 1.8915 0.2534
0.9877 0.6369 1800 1.8091 0.2624
1.21 0.7077 2000 1.7322 0.2552
1.5582 0.7785 2200 1.6645 0.2445
1.1392 0.8493 2400 1.6458 0.2294
1.8181 0.9200 2600 1.5874 0.2313
1.2517 0.9908 2800 1.5736 0.2361
1.2004 1.0616 3000 1.5693 0.2344
1.4357 1.1323 3200 1.5447 0.2190
1.1354 1.2031 3400 1.4577 0.3232
0.853 1.2739 3600 1.4034 0.2166
1.4631 1.3447 3800 1.4105 0.2093
2.3234 1.4154 4000 1.3813 0.2044
0.6976 1.4862 4200 1.3505 0.2088
1.4337 1.5570 4400 1.3338 0.2079
1.0502 1.6277 4600 1.3044 0.1900
1.2216 1.6985 4800 1.2883 0.2176
1.0111 1.7693 5000 1.2530 0.1977
0.9992 1.8401 5200 1.2245 0.2064
0.9941 1.9108 5400 1.2187 0.1933
1.4861 1.9816 5600 1.1961 0.1827
1.1703 2.0524 5800 1.1776 0.1927
0.8935 2.1231 6000 1.1617 0.1891
2.5386 2.1939 6200 1.1686 0.1823
0.4705 2.2647 6400 1.1259 0.1843
1.2777 2.3355 6600 1.1228 0.1882
0.6823 2.4062 6800 1.1035 0.1787
1.2498 2.4770 7000 1.0976 0.1814
0.4579 2.5478 7200 1.0839 0.1721
0.9005 2.6185 7400 1.0695 0.1817
0.8045 2.6893 7600 1.0513 0.1745
1.3044 2.7601 7800 1.0336 0.1814
1.0797 2.8309 8000 1.0275 0.1846
0.3826 2.9016 8200 1.0178 0.1817
0.6175 2.9724 8400 1.0124 0.1764

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1