metadata

tags: autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - abhishek/autonlp-data-bbc-news-classification
co2_eq_emissions: 5.448567309047846

Model Trained Using AutoNLP

Problem type: Multi-class Classification
Model ID: 37229289
CO2 Emissions (in grams): 5.448567309047846

Validation Metrics

Loss: 0.07081354409456253
Accuracy: 0.9867109634551495
Macro F1: 0.9859067529980614
Micro F1: 0.9867109634551495
Weighted F1: 0.9866417220968429
Macro Precision: 0.9868771404595043
Micro Precision: 0.9867109634551495
Weighted Precision: 0.9869289511551576
Macro Recall: 0.9853173241852486
Micro Recall: 0.9867109634551495
Weighted Recall: 0.9867109634551495

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 AutoNLP"}' https://api-inference.huggingface.co/models/abhishek/autonlp-bbc-news-classification-37229289

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("abhishek/autonlp-bbc-news-classification-37229289", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("abhishek/autonlp-bbc-news-classification-37229289", use_auth_token=True)

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

outputs = model(**inputs)