beit_large512_fine_tuned

This model is a fine-tuned version of microsoft/beit-base-patch16-384 on the beans dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0353
  • Accuracy: 0.9925

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: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • 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
4.6571 0.98 16 0.3870 0.8722
0.2299 1.97 32 0.0632 0.9850
0.1435 2.95 48 0.0353 0.9925

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cpu
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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Dataset used to train Thamer/beit_large512_fine_tuned

Evaluation results