---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fashion_classifier
  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. -->

# fashion_classifier

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: 0.8857
- Accuracy: 0.8018

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.2283        | 0.9882 | 21   | 2.1148          | 0.4852   |
| 1.853         | 1.9765 | 42   | 1.6702          | 0.7249   |
| 1.4363        | 2.9647 | 63   | 1.3298          | 0.7367   |
| 1.1618        | 4.0    | 85   | 1.1528          | 0.7604   |
| 0.9739        | 4.9882 | 106  | 1.0281          | 0.7811   |
| 0.8778        | 5.9765 | 127  | 0.9325          | 0.7929   |
| 0.8114        | 6.9647 | 148  | 0.9100          | 0.8136   |
| 0.7626        | 8.0    | 170  | 0.9288          | 0.7633   |
| 0.691         | 8.9882 | 191  | 0.9058          | 0.7870   |
| 0.6988        | 9.8824 | 210  | 0.8857          | 0.8018   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1