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| Label | Precision | Recall | F1 | Support |
|---|---|---|---|---|
| cancel_order | 1.00 | 1.00 | 1.00 | 22 |
| damaged_item | 1.00 | 1.00 | 1.00 | 23 |
| delivery_complaint | 0.83 | 0.87 | 0.85 | 23 |
| discount_query | 1.00 | 1.00 | 1.00 | 23 |
| exchange_product | 1.00 | 1.00 | 1.00 | 21 |
| other | 1.00 | 1.00 | 1.00 | 19 |
| payment_issue | 1.00 | 1.00 | 1.00 | 23 |
| product_availability | 1.00 | 1.00 | 1.00 | 23 |
| product_information | 1.00 | 1.00 | 1.00 | 21 |
| refund_status | 1.00 | 1.00 | 1.00 | 23 |
| return_request | 1.00 | 1.00 | 1.00 | 23 |
| track_order | 0.95 | 0.82 | 0.88 | 22 |
| wrong_item | 0.91 | 1.00 | 0.95 | 21 |
1from transformers import pipeline
2
3classifier = pipeline(
4 "text-classification",
5 model="Hari5115/hinglish-retail-intent-classifier"
6)
7
8result = classifier("mera order kab aayega?")
9print(result)
10# [{'label': 'track_order', 'score': 0.96}]| Label | Description |
|---|---|
track_order | Customer asking where their order is or when it arrives |
cancel_order | Customer wants to cancel a placed order |
exchange_product | Customer received wrong size/colour, wants a swap |
refund_status | Customer asking about refund timeline or whether it was processed |
delivery_complaint | Late delivery, not delivered, delivery agent issue |
damaged_item | Product arrived broken, damaged, or defective |
wrong_item | Completely wrong product was delivered |
return_request | Customer wants to return a product |
payment_issue | Money deducted but order not placed, double charge |
product_availability | Asking if an item is in stock or available in a size/colour |
product_information | Asking about product details, material, dimensions |
discount_query | Promo code not working, coupon issues, asking for discount |
other | Anything that does not fit the above |
google/muril-base-cased