README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: I love AutoTrain
datasets:
  - yeye776/autotrain-data-intent-classification-5categories-bert-kor-base
co2_eq_emissions:
  emissions: 0.03180363801413368

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 90853144392
• CO2 Emissions (in grams): 0.0318

Validation Metrics

• Loss: 0.078
• Accuracy: 0.963
• Macro F1: 0.949
• Micro F1: 0.963
• Weighted F1: 0.964
• Macro Precision: 0.950
• Micro Precision: 0.963
• Weighted Precision: 0.972
• Macro Recall: 0.960
• Micro Recall: 0.963
• Weighted Recall: 0.963

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-5categories-bert-kor-base-90853144392

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("yeye776/autotrain-intent-classification-5categories-bert-kor-base-90853144392", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("yeye776/autotrain-intent-classification-5categories-bert-kor-base-90853144392", use_auth_token=True)

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

outputs = model(**inputs)