thuyentruong/food_classification_model

google/vit-base-patch16-224-in21k-v2-finetuned

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the food101 dataset. It achieves the following results on the evaluation set:

• Loss: 1.0612
• Accuracy: 0.7969

Model description

• Model type: Language model
• Language(s) (NLP): English
• License: Apache 2.0
• Related Model: google/vit-base-patch16-224-in21k
• Original Checkpoints: google/vit-base-patch16-224-in21k
• Resources for more information: Research paper

Intended uses & limitations

This model can be used to classify what type of food in the image provided.

Training and evaluation data

The model was trained on food101 dataset with 80:20 train-test-split.

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: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.9201	1.0	947	1.9632	0.7297
1.2002	2.0	1894	1.2327	0.7805
0.9561	3.0	2841	1.0612	0.7969

Framework versions

• Transformers 4.40.2
• Pytorch 2.4.0+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1