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swin-food102

This model is a fine-tuned version of juliensimon/autotrain-food101-1471154053 on the food102 dataset, namely the food101 dataset with an extra class generated with a Stable Diffusion model.

A detailed walk-through is available on YouTube.

The achieves the following results on the evaluation set:

  • Loss: 0.2510
  • Accuracy: 0.9338

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.1648 1.0 597 0.3118 0.9218
0.31 2.0 1194 0.2606 0.9322
0.2488 3.0 1791 0.2510 0.9338

Framework versions

  • Transformers 4.23.1
  • Pytorch 1.12.1+cu102
  • Datasets 2.4.0
  • Tokenizers 0.13.1
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Dataset used to train juliensimon/swin-food102