README.md

metadata

tags: autonlp
language: fr
widget:
  - text: I love AutoNLP 🤗
datasets:
  - mazancourt/autonlp-data-politics-sentence-classifier
co2_eq_emissions: 1.06099358268878

Model Trained Using AutoNLP

• Problem type: Multi-class Classification
• Model ID: 23105051
• CO2 Emissions (in grams): 1.06099358268878

Validation Metrics

• Loss: 0.6050735712051392
• Accuracy: 0.8097826086956522
• Macro F1: 0.7713543865034599
• Micro F1: 0.8097826086956522
• Weighted F1: 0.8065488494385247
• Macro Precision: 0.7861074705111403
• Micro Precision: 0.8097826086956522
• Weighted Precision: 0.806470454156932
• Macro Recall: 0.7599656456873758
• Micro Recall: 0.8097826086956522
• Weighted Recall: 0.8097826086956522

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/mazancourt/autonlp-politics-sentence-classifier-23105051

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("mazancourt/autonlp-politics-sentence-classifier-23105051", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("mazancourt/autonlp-politics-sentence-classifier-23105051", use_auth_token=True)

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

outputs = model(**inputs)