readme: ---
  tags: autonlp
  language: en
  widget:
  - text: "I love AutoNLP 🤗"
  datasets:
  - bitmorse/autonlp-data-ks
  co2_eq_emissions: 2.2247356264808964
  ---
  
  # Model Trained Using AutoNLP
  
  - Problem type: Multi-class Classification
  - Model ID: 530615016
  - CO2 Emissions (in grams): 2.2247356264808964
  
  ## Validation Metrics
  
  - Loss: 0.7859578132629395
  - Accuracy: 0.676854818831649
  - Macro F1: 0.3297126297995653
  - Micro F1: 0.676854818831649
  - Weighted F1: 0.6429522696884535
  - Macro Precision: 0.33152557743856437
  - Micro Precision: 0.676854818831649
  - Weighted Precision: 0.6276125515413322
  - Macro Recall: 0.33784302289888885
  - Micro Recall: 0.676854818831649
  - Weighted Recall: 0.676854818831649
  
  
  ## 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/bitmorse/autonlp-ks-530615016
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("bitmorse/autonlp-ks-530615016", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("bitmorse/autonlp-ks-530615016", use_auth_token=True)
  
  inputs = tokenizer("I love AutoNLP", return_tensors="pt")
  
  outputs = model(**inputs)
  ```