--- 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: 0.4507 - eval_accuracy: 0.8863 - eval_runtime: 156.5229 - eval_samples_per_second: 96.791 - eval_steps_per_second: 6.05 - epoch: 49.63 - step: 47000 ## 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