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# my_awesome_food_model

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the food101 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6405
- Precision: 0.8856
- Recall: 0.887
- F1: 0.8819
- Accuracy: 0.887

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 2.7494        | 0.99  | 62   | 2.5554          | 0.7488    | 0.829  | 0.7859 | 0.829    |
| 1.9011        | 2.0   | 125  | 1.8058          | 0.8825    | 0.878  | 0.8645 | 0.878    |
| 1.6532        | 2.98  | 186  | 1.6405          | 0.8856    | 0.887  | 0.8819 | 0.887    |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["food101"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "my_awesome_food_model", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "food101", "type": "food101", "config": "default", "split": "train[:5000]", "args": "default"}, "metrics": [{"type": "precision", "value": 0.8855567868882221, "name": "Precision"}, {"type": "recall", "value": 0.887, "name": "Recall"}, {"type": "f1", "value": 0.8818977914615195, "name": "F1"}, {"type": "accuracy", "value": 0.887, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard vit image-classification generated_from_trainer dataset:food101 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us