---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vogue-fashion-collection-15
  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. -->

# vogue-fashion-collection-15

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: 0.1795
- Accuracy: 0.9454

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.6546        | 1.0   | 1094  | 1.8069          | 0.8558   |
| 0.8991        | 2.0   | 2189  | 0.9520          | 0.8966   |
| 0.589         | 3.0   | 3283  | 0.5906          | 0.9158   |
| 0.4017        | 4.0   | 4378  | 0.4167          | 0.9273   |
| 0.2594        | 5.0   | 5472  | 0.3189          | 0.9358   |
| 0.308         | 6.0   | 6567  | 0.2758          | 0.9363   |
| 0.2114        | 7.0   | 7661  | 0.2338          | 0.9419   |
| 0.1439        | 8.0   | 8756  | 0.2131          | 0.9443   |
| 0.1568        | 9.0   | 9850  | 0.1943          | 0.9454   |
| 0.1388        | 10.0  | 10940 | 0.1795          | 0.9454   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0