metadata

tags: autotrain
language: en
widget:
  - text: >-
      Ending all forms of discrimination against women and girls is not only a
      basic human right, but it also crucial to accelerating sustainable
      development. It has been proven time and again, that empowering women and
      girls has a multiplier effect, and helps drive up economic growth and
      development across the board.

      Since 2000, UNDP, together with our UN partners and the rest of the global
      community, has made gender equality central to our work. We have seen
      remarkable progress since then. More girls are now in school compared to
      15 years ago, and most regions have reached gender parity in primary
      education. Women now make up to 41 percent of paid workers outside of
      agriculture, compared to 35 percent in 1990.
datasets:
  - jonas/autotrain-data-osdg-sdg-classifier
co2_eq_emissions: 0.0653263174784986

Model Trained Using AutoTrain

Problem type: Multi-class Classification
Model ID: 900229515
CO2 Emissions (in grams): 0.0653263174784986

Validation Metrics

Loss: 0.3644874095916748
Accuracy: 0.8972544579677328
Macro F1: 0.8500873710954522
Micro F1: 0.8972544579677328
Weighted F1: 0.8937529692986061
Macro Precision: 0.8694369727467804
Micro Precision: 0.8972544579677328
Weighted Precision: 0.8946984684977016
Macro Recall: 0.8405065997404059
Micro Recall: 0.8972544579677328
Weighted Recall: 0.8972544579677328

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/jonas/autotrain-osdg-sdg-classifier-900229515

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("jonas/autotrain-osdg-sdg-classifier-900229515", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("jonas/autotrain-osdg-sdg-classifier-900229515", use_auth_token=True)

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

outputs = model(**inputs)