CoolFace
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aabdumalikov/image-classification-v1

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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Model Card

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

  • Loss: 2.3870
  • Accuracy: 0.5658

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: 32
  • evalbatchsize: 32
  • seed: 42
  • gradientaccumulationsteps: 2
  • totaltrainbatch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • lrschedulerwarmup_ratio: 0.1
  • num_epochs: 10
  • mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracy
4.75261.06124.74740.2541
3.95742.012243.87940.4050
3.46653.018363.38520.4621
3.00174.024483.05510.4944
2.72175.030602.82510.5137
2.57526.036722.65690.5399
2.50647.042842.54470.5501
2.39568.048962.44930.5631
2.17689.055082.40400.5631
2.216810.061202.38700.5658

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1