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BEiT-finetuned

This model is a fine-tuned version of microsoft/beit-base-patch16-224 on the cifar10 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0256
  • Accuracy: 0.9918

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: 3e-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
0.3296 1.0 351 0.0492 0.9862
0.2353 2.0 702 0.0331 0.9894
0.2127 3.0 1053 0.0256 0.9918

Framework versions

  • Transformers 4.19.2
  • Pytorch 1.11.0+cu113
  • Datasets 2.2.1
  • Tokenizers 0.12.1
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Dataset used to train jadohu/BEiT-finetuned

Evaluation results