87

This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the cifar10 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5088
  • Accuracy: 0.9734
  • Dt Accuracy: 0.9734
  • Df Accuracy: 0.983
  • Unlearn Overall Accuracy: 0.2091
  • Unlearn Time: None

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: 0.0001
  • train_batch_size: 128
  • eval_batch_size: 256
  • seed: 87
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Overall Accuracy Unlearn Overall Accuracy Time
No log 1.0 16 0.3339 0.982 0.2107 0.2107 None
No log 2.0 32 0.4119 0.98 0.2138 0.2138 None
No log 3.0 48 0.6311 0.969 0.2309 0.2309 None
No log 4.0 64 0.4788 0.985 0.2059 0.2059 None
No log 5.0 80 0.5297 0.981 0.2123 0.2123 None
No log 6.0 96 0.4680 0.982 0.2107 0.2107 None
No log 7.0 112 0.6570 0.978 0.2170 0.2170 None
No log 8.0 128 0.5795 0.981 0.2122 0.2122 None
No log 9.0 144 0.5085 0.983 0.2091 0.2091 None
No log 10.0 160 0.5088 0.983 0.2091 0.2091 None

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.0
  • Tokenizers 0.15.2
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