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nehaMe123/trocr-medical-v1-optimized

sourceHugging Faceupdated 8mo agoView on Hugging Face
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Model Card

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trocr-medical-v1-optimized

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

  • —Loss: 0.0500
  • —Cer: 0.3118

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: 4e-05
  • —trainbatchsize: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 15
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossCer
1.13841.01760.80870.2478
0.29742.03520.22460.2590
0.19633.05280.17780.2712
0.12064.07040.15060.2616
0.07065.08800.12750.2052
0.04136.010560.12010.2565
0.02917.012320.09870.2397
0.01368.014080.07230.2641
0.019.015840.06430.3012
0.002610.017600.06300.2641
0.004911.019360.06180.3586
0.000812.021120.04860.3118
0.000813.022880.04260.3255
0.000414.024640.04870.3098
0.001315.026400.05000.3118

Framework versions

  • —Transformers 4.57.1
  • —Pytorch 2.8.0+cu126
  • —Datasets 4.4.2
  • —Tokenizers 0.22.1