---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: food_classifier_2025_01_31_00_04
  results: []
---

<!-- 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. -->

# food_classifier_2025_01_31_00_04

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4920
- Accuracy: 0.8763

## 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: 0.0005
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 2048
- total_eval_batch_size: 512
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.9401        | 1.0   | 37   | 3.1519          | 0.7044   |
| 1.5951        | 2.0   | 74   | 1.1581          | 0.7973   |
| 0.916         | 3.0   | 111  | 0.7583          | 0.8228   |
| 0.7189        | 4.0   | 148  | 0.6624          | 0.8371   |
| 0.5926        | 5.0   | 185  | 0.6070          | 0.8476   |
| 0.5456        | 6.0   | 222  | 0.5709          | 0.8553   |
| 0.4675        | 7.0   | 259  | 0.5564          | 0.8572   |
| 0.4246        | 8.0   | 296  | 0.5465          | 0.8602   |
| 0.3732        | 9.0   | 333  | 0.5401          | 0.8627   |
| 0.333         | 10.0  | 370  | 0.5197          | 0.8671   |
| 0.3067        | 11.0  | 407  | 0.5077          | 0.8712   |
| 0.2872        | 12.0  | 444  | 0.5090          | 0.8702   |
| 0.2537        | 13.0  | 481  | 0.5066          | 0.8761   |
| 0.2496        | 14.0  | 518  | 0.5004          | 0.8750   |
| 0.2282        | 15.0  | 555  | 0.4920          | 0.8763   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1
- Datasets 2.19.1
- Tokenizers 0.21.0