Albert-bbc-news / README.md
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metadata
tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - AyoubChLin/autotrain-data-albert-bbc-news
co2_eq_emissions:
  emissions: 13.344689233410659

Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 48939118438
  • CO2 Emissions (in grams): 13.3447

Validation Metrics

  • Loss: 0.103
  • Accuracy: 0.978
  • Macro F1: 0.978
  • Micro F1: 0.978
  • Weighted F1: 0.978
  • Macro Precision: 0.977
  • Micro Precision: 0.978
  • Weighted Precision: 0.978
  • Macro Recall: 0.978
  • Micro Recall: 0.978
  • Weighted Recall: 0.978

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/AyoubChLin/autotrain-albert-bbc-news-48939118438

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("AyoubChLin/autotrain-albert-bbc-news-48939118438", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("AyoubChLin/autotrain-albert-bbc-news-48939118438", use_auth_token=True)

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

outputs = model(**inputs)