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