---
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: "익일 화물 알려줘"
datasets:
- yeye776/autotrain-data-intent-classification-6categories-distilbert
co2_eq_emissions:
  emissions: 0.4747647804932346
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 89087143849
- CO2 Emissions (in grams): 0.4748

## Validation Metrics

- Loss: 0.542
- Accuracy: 0.881
- Macro F1: 0.833
- Micro F1: 0.881
- Weighted F1: 0.854
- Macro Precision: 0.918
- Micro Precision: 0.881
- Weighted Precision: 0.901
- Macro Recall: 0.846
- Micro Recall: 0.881
- Weighted Recall: 0.881

## 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-distilbert-89087143849
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("yeye776/autotrain-intent-classification-6categories-distilbert-89087143849", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("yeye776/autotrain-intent-classification-6categories-distilbert-89087143849", use_auth_token=True)

inputs = tokenizer("I love AutoTrain", return_tensors="pt")

outputs = model(**inputs)
```