---
license: cc-by-4.0
base_model: distilbert-base-uncased
library_name: transformers
tags:
- text-classification
- fashion
- product-categorization
- indian-ecommerce
language:
- en
---
# Fashion Category Classifier
DistilBERT fine-tuned to classify Indian fashion product titles into 11 categories.

## Credits
Built on [DistilBERT](https://huggingface.co/distilbert/distilbert-base-uncased) by Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf (Hugging Face), licensed under [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0).

## Labels
`Tops` `Bottoms` `Dresses` `Outerwear` `Footwear` `Bags` `Jewellery` `Ethnicwear` `Activewear` `Innerwear` `Headwear`

## Usage
```python
from transformers import pipeline
clf = pipeline("text-classification", model="roaringguts/DistilBERT")
clf("Nike Dry Fit Running Tshirt")
# [{'label': 'Activewear', 'score': 0.99}]
# batch
clf(["Lavie Women Tote Bag", "Malabar Gold Plated Necklace", "Clarks Oxford Shoes"])
```

## Training
- **Base model:** `distilbert-base-uncased`
- **Dataset:** ~63k real product titles from Myntra + synthetic samples generated for underrepresented categories
- **Split:** 80/10/10 train/val/test, stratified
- **Epochs:** 5 (early stopping, patience 2)
- **Batch size:** 64
- **Learning rate:** 3e-5
- **Precision:** fp16

## Evaluation
Evaluated on a held-out stratified test set.

| Metric | Score |
|--------|-------|
| Accuracy | **99.27%** |

## Limitations
- Trained on Indian e-commerce titles — may underperform on Western brand naming conventions
- Ethnicwear and Innerwear have some overlap (e.g. sports bras vs regular bras)
- Low sample count for Bags and Headwear in original data, partially filled with synthetic titles

## License
This model is released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). The base DistilBERT weights it derives from are licensed under Apache 2.0.