---
library_name: transformers
license: apache-2.0
base_model: google/vit-large-patch16-384
tags:
- image-classification
- vision
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: fashion-images-pack-types-vit-large-patch16-384-v1
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: touchtech/fashion-images-pack-types
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.989983305509182
---

<!-- 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-images-pack-types-vit-large-patch16-384-v1

This model is a fine-tuned version of [google/vit-large-patch16-384](https://huggingface.co/google/vit-large-patch16-384) on the touchtech/fashion-images-pack-types dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0446
- Accuracy: 0.9900

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0823        | 1.0   | 1697 | 0.0661          | 0.9837   |
| 0.0197        | 2.0   | 3394 | 0.0900          | 0.9812   |
| 0.015         | 3.0   | 5091 | 0.0446          | 0.9900   |
| 0.0017        | 4.0   | 6788 | 0.0518          | 0.9912   |
| 0.0           | 5.0   | 8485 | 0.0485          | 0.9917   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0