readme: ---
  tags: autonlp
  language: unk
  widget:
  - text: "I love AutoNLP 🤗"
  datasets:
  - gabitoo1234/autonlp-data-mut_uchile
  co2_eq_emissions: 43.078469852595994
  ---
  
  # Model Trained Using AutoNLP
  
  - Problem type: Multi-class Classification
  - Model ID: 640218740
  - CO2 Emissions (in grams): 43.078469852595994
  
  ## Validation Metrics
  
  - Loss: 0.8302136063575745
  - Accuracy: 0.7887341933835739
  - Macro F1: 0.5756730305293746
  - Micro F1: 0.7887341933835739
  - Weighted F1: 0.7878942570915727
  - Macro Precision: 0.620883634472996
  - Micro Precision: 0.7887341933835739
  - Weighted Precision: 0.8009430092038783
  - Macro Recall: 0.5521761315904072
  - Micro Recall: 0.7887341933835739
  - Weighted Recall: 0.7887341933835739
  
  
  ## 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/gabitoo1234/autonlp-mut_uchile-640218740
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("gabitoo1234/autonlp-mut_uchile-640218740", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("gabitoo1234/autonlp-mut_uchile-640218740", use_auth_token=True)
  
  inputs = tokenizer("I love AutoNLP", return_tensors="pt")
  
  outputs = model(**inputs)
  ```