readme: ---
  tags: autotrain
  language: unk
  widget:
  - text: "I love AutoTrain 🤗"
  datasets:
  - Amalq/autotrain-data-smm4h_large_roberta_clean
  co2_eq_emissions: 9.123490454955585
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Binary Classification
  - Model ID: 874027878
  - CO2 Emissions (in grams): 9.123490454955585
  
  ## Validation Metrics
  
  - Loss: 0.35724225640296936
  - Accuracy: 0.8571428571428571
  - Precision: 0.7637362637362637
  - Recall: 0.8910256410256411
  - AUC: 0.9267555361305361
  - F1: 0.8224852071005917
  
  ## 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/Amalq/autotrain-smm4h_large_roberta_clean-874027878
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("Amalq/autotrain-smm4h_large_roberta_clean-874027878", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("Amalq/autotrain-smm4h_large_roberta_clean-874027878", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```