---
license: apache-2.0
base_model: microsoft/swin-base-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- food101
metrics:
- accuracy
model-index:
- name: swin-base-patch4-window7-224-food101-24-12
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: food101
      type: food101
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9312475247524753
---

<!-- 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. -->

# swin-base-patch4-window7-224-food101-24-12

This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on the food101 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2529
- Accuracy: 0.9312

## 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: 24
- eval_batch_size: 24
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9481        | 1.0   | 789  | 0.4713          | 0.8665   |
| 0.7584        | 2.0   | 1578 | 0.3561          | 0.8985   |
| 0.7081        | 3.0   | 2367 | 0.3190          | 0.9058   |
| 0.5639        | 4.0   | 3157 | 0.2951          | 0.9127   |
| 0.5106        | 5.0   | 3946 | 0.2863          | 0.9190   |
| 0.4633        | 6.0   | 4735 | 0.2785          | 0.9211   |
| 0.4188        | 7.0   | 5524 | 0.2704          | 0.9240   |
| 0.3308        | 8.0   | 6314 | 0.2739          | 0.9226   |
| 0.3853        | 9.0   | 7103 | 0.2634          | 0.9263   |
| 0.2281        | 10.0  | 7892 | 0.2578          | 0.9283   |
| 0.2648        | 11.0  | 8681 | 0.2586          | 0.9288   |
| 0.2303        | 12.0  | 9468 | 0.2529          | 0.9312   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1