readme: ---
  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/osdg_sdg_data_processed
  co2_eq_emissions: 0.0653263174784986
  ---
  # About
  
  Machine Learning model for classifying text according to the first 15 of the 17 Sustainable Development Goals from the United Nations. Note that model is trained on quite short paragraphs (around 100 words) and performs best with similar input sizes. 
  
  Data comes from the amazing https://osdg.ai/ community!
  
  * There is an improved version (finetuned Roberta) of the model available here: https://huggingface.co/jonas/roberta-base-finetuned-sdg
  
  # Model Training Specifics 
  
  - 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/sdg_classifier_osdg", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("jonas/sdg_classifier_osdg", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```