---
license: apache-2.0
base_model: jessicagabriel/my_awesome_food_model
tags:
- generated_from_trainer
datasets:
- food101
metrics:
- accuracy
model-index:
- name: my_awesome_food_model
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: food101
      type: food101
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8900990099009901
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# my_awesome_food_model

This model is a fine-tuned version of [jessicagabriel/my_awesome_food_model](https://huggingface.co/jessicagabriel/my_awesome_food_model) on the food101 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4388
- Accuracy: 0.8901

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4631        | 1.0   | 947  | 0.4695          | 0.8811   |
| 0.4759        | 2.0   | 1894 | 0.5028          | 0.8700   |
| 0.3744        | 3.0   | 2841 | 0.4840          | 0.8754   |
| 0.3198        | 4.0   | 3788 | 0.4823          | 0.8769   |
| 0.3655        | 5.0   | 4735 | 0.4658          | 0.8815   |
| 0.2994        | 6.0   | 5682 | 0.4854          | 0.8770   |
| 0.2268        | 7.0   | 6629 | 0.4617          | 0.8837   |
| 0.2735        | 8.0   | 7576 | 0.4479          | 0.8874   |
| 0.1579        | 9.0   | 8523 | 0.4487          | 0.8874   |
| 0.2327        | 10.0  | 9470 | 0.4388          | 0.8901   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3