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---
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-nobg
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-nobg
## Model description
This model classifies an image into a fashion collection. It is trained on the [tonyassi/vogue-runway-top15-512px-nobg](https://huggingface.co/datasets/tonyassi/vogue-runway-top15-512px-nobg) dataset and fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k).
Because the model trained on a dataset with white background it is suggested to only give the model an image with a white background. Removing the background allows the model to focus on the clothes and disregard the background.
## Dataset description
[tonyassi/vogue-runway-top15-512px-nobg](https://huggingface.co/datasets/tonyassi/vogue-runway-top15-512px-nobg)
- 15 fashion houses
- 1679 collections
- 87,547 images
- No background
### How to use
```python
from transformers import pipeline
# Initialize image classification pipeline
pipe = pipeline("image-classification", model="tonyassi/vogue-fashion-collection-15-nobg")
# Perform classification
result = pipe('image.png')
# Print results
print(result)
```
## Training and evaluation data
It achieves the following results on the evaluation set:
- Loss: 0.5880
- Accuracy: 0.8403
### 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
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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