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msi-efficientnet-pretrain

This model is a fine-tuned version of google/efficientnet-b0 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4941
  • Accuracy: 0.8613

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
0.317 1.0 781 0.9029 0.7535
0.2009 2.0 1562 0.4094 0.8840
0.1405 3.0 2343 0.4941 0.8613

Framework versions

  • Transformers 4.36.0
  • Pytorch 2.0.1+cu117
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Evaluation results