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Dugerij/image_segmentation_classifier

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
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Model Card

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imagesegmentationclassifier

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the taresco/newspaper_ocr dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0033
  • —Accuracy: 0.9993

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
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 1337
  • —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 5.0

Training results

Training LossEpochStepValidation LossAccuracy
0.00141.020310.00650.9986
0.00052.040620.00330.9993
0.00033.060930.00580.9990
0.00024.081240.00430.9983
0.00015.0101550.00360.9990

Framework versions

  • —Transformers 4.52.0.dev0
  • —Pytorch 2.6.0+cu124
  • —Datasets 3.5.0
  • —Tokenizers 0.21.0