readme: ---
  tags: autonlp
  language: en
  widget:
  - text: "I love AutoNLP 🤗"
  datasets:
  - DrishtiSharma/autonlp-data-Text-Classification-Catalonia-Independence-AutoNLP
  co2_eq_emissions: 3.622203603306694
  ---
  
  # Model Trained Using AutoNLP
  
  - Problem type: Multi-class Classification
  - Model ID: 633018323
  - CO2 Emissions (in grams): 3.622203603306694
  
  ## Validation Metrics
  
  - Loss: 0.681106686592102
  - Accuracy: 0.709136109384711
  - Macro F1: 0.6987186860138147
  - Micro F1: 0.709136109384711
  - Weighted F1: 0.7059639788836748
  - Macro Precision: 0.7174345617951404
  - Micro Precision: 0.709136109384711
  - Weighted Precision: 0.712710833401347
  - Macro Recall: 0.6912117894374218
  - Micro Recall: 0.709136109384711
  - Weighted Recall: 0.709136109384711
  
  
  ## 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/DrishtiSharma/autonlp-Text-Classification-Catalonia-Independence-AutoNLP-633018323
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("DrishtiSharma/autonlp-Text-Classification-Catalonia-Independence-AutoNLP-633018323", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("DrishtiSharma/autonlp-Text-Classification-Catalonia-Independence-AutoNLP-633018323", use_auth_token=True)
  
  inputs = tokenizer("I love AutoNLP", return_tensors="pt")
  
  outputs = model(**inputs)
  ```