APNR-Braincore-V2 / README.md
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metadata
library_name: transformers
base_model: microsoft/trocr-base-str
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: microsoft/trocr-base-str
    results: []

microsoft/trocr-base-str

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

  • Loss: 0.0856
  • Cer: 0.0098
  • Wer: 0.0573

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer Wer
1.6623 1.0 217 0.4722 0.0574 0.2340
0.4122 2.0 434 0.3248 0.0378 0.1585
0.1077 3.0 651 0.0898 0.0132 0.0722
0.047 4.0 868 0.0848 0.0114 0.0614
0.0304 5.0 1085 0.0836 0.0122 0.0634
0.0224 6.0 1302 0.0891 0.0104 0.0566
0.0154 7.0 1519 0.0873 0.0107 0.0587
0.0137 8.0 1736 0.0852 0.0102 0.0560
0.0121 9.0 1953 0.0883 0.0107 0.0634
0.0095 10.0 2170 0.0829 0.0092 0.0526
0.0068 11.0 2387 0.0851 0.0091 0.0519
0.0075 12.0 2604 0.0831 0.0102 0.0600
0.0055 13.0 2821 0.0824 0.0098 0.0580
0.0048 14.0 3038 0.0821 0.0099 0.0587
0.0023 15.0 3255 0.0873 0.0096 0.0553
0.0018 16.0 3472 0.0835 0.0102 0.0593
0.0016 17.0 3689 0.0888 0.0100 0.0600
0.0034 18.0 3906 0.0853 0.0094 0.0553
0.001 19.0 4123 0.0857 0.0096 0.0566
0.0013 20.0 4340 0.0856 0.0098 0.0573

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 2.17.0
  • Tokenizers 0.19.1