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metadata
tags:
  - generated_from_trainer
datasets:
  - food101
model-index:
  - name: food-image-classification
    results: []

food-image-classification

This model was trained from scratch on the food101 dataset It achieves the following results on the evaluation set:

  • eval_loss: 0.4645
  • eval_accuracy: 0.8831
  • eval_runtime: 156.6057
  • eval_samples_per_second: 96.74
  • eval_steps_per_second: 6.047
  • epoch: 54.91
  • step: 52000

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: 500

Framework versions

  • Transformers 4.37.0
  • Pytorch 2.1.2
  • Datasets 2.1.0
  • Tokenizers 0.15.1