CoolFace
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TicoRaph/vit-pulp-fiction-characters-photos

sourceHugging Faceapache-2.0updated 19d agoView on Hugging Face
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Model Card

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vit-pulp-fiction-characters-photos

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

  • —Loss: 0.9006
  • —Accuracy: 0.8971

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
  • —trainbatchsize: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 64
  • —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: 10

Training results

Training LossEpochStepValidation LossAccuracy
No log1.051.69240.6471
1.68712.0101.48930.7206
1.68713.0151.33510.7794
1.22504.0201.21590.7794
1.22505.0251.11700.8088
0.94656.0301.03520.8382
0.94657.0350.97520.8529
0.81518.0400.93490.8824
0.81519.0450.91000.8824
0.711610.0500.90060.8971

Framework versions

  • —Transformers 5.16.1
  • —Pytorch 2.14.0
  • —Datasets 5.0.1
  • —Tokenizers 0.23.2