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Tianmu28/mammals_multiclass_classification

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

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mammalsmulticlassclassification

This model is a fine-tuned version of google/vit-base-patch16-224 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2452
  • Accuracy: 0.9496

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
  • optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: linear
  • num_epochs: 15

Training results

Training LossEpochStepValidation LossAccuracy
0.55011.03940.36970.9207
0.07572.07880.28940.9311
0.0343.011820.28650.9304
0.00434.015760.26100.9385
0.00245.019700.25260.9415
0.00076.023640.24520.9496
0.00067.027580.24320.9481
0.00048.031520.24420.9481
0.00049.035460.24840.9496
0.000310.039400.25450.9467
0.000311.043340.25430.9481

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3