metadata
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: 익일 화물 알려줘
datasets:
- yeye776/autotrain-data-intent-classification-6categories-bertkorbase
co2_eq_emissions:
emissions: 0.4074326029231982
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 89098143855
- CO2 Emissions (in grams): 0.4074
Validation Metrics
- Loss: 0.052
- Accuracy: 0.976
- Macro F1: 0.973
- Micro F1: 0.976
- Weighted F1: 0.975
- Macro Precision: 0.983
- Micro Precision: 0.976
- Weighted Precision: 0.979
- Macro Recall: 0.967
- Micro Recall: 0.976
- Weighted Recall: 0.976
Dataset Label
| Label | intent(category) |
|---|---|
| 11 | 날씨 |
| 12 | 장소안내 |
| 13 | 전화연결 |
| 14 | 일상대화 |
| 15 | 화물추천 |
| 16 | 검색(FAQ) |
Usage
You can use cURL to access this model:
$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/yeye776/autotrain-intent-classification-6categories-bertkorbase-89098143855
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("yeye776/autotrain-intent-classification-6categories-bertkorbase-89098143855", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("yeye776/autotrain-intent-classification-6categories-bertkorbase-89098143855", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)