Prot10 / swin-tiny-patch4-window7-224-for-pre_evaluation

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Model's Last Updated: August 30 2023
image-classification

Introduction of swin-tiny-patch4-window7-224-for-pre_evaluation

Model Details of swin-tiny-patch4-window7-224-for-pre_evaluation

swin-tiny-patch4-window7-224-for-pre_evaluation

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5062
  • Accuracy: 0.3287
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
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3
Training results
Training Loss Epoch Step Validation Loss Accuracy
1.579 0.93 10 1.5190 0.3170
1.4951 1.95 21 1.5104 0.3124
1.4951 2.79 30 1.5062 0.3287
Framework versions
  • Transformers 4.32.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3

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Updated:June 05 2023