readme: ---
  tags: autotrain
  language: en
  widget:
  - text: "I love AutoTrain 🤗"
  datasets:
  - xInsignia/autotrain-data-Online_orders-5cf92320
  co2_eq_emissions: 2.4120667129093043
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 755323156
  - CO2 Emissions (in grams): 2.4120667129093043
  
  ## Validation Metrics
  
  - Loss: 0.17826060950756073
  - Accuracy: 0.9550898203592815
  - Macro F1: 0.8880388927888968
  - Micro F1: 0.9550898203592815
  - Weighted F1: 0.9528256324309916
  - Macro Precision: 0.9093073732635162
  - Micro Precision: 0.9550898203592815
  - Weighted Precision: 0.9533674643333371
  - Macro Recall: 0.8872729481745715
  - Micro Recall: 0.9550898203592815
  - Weighted Recall: 0.9550898203592815
  
  
  ## 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/xInsignia/autotrain-Online_orders-755323156
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("xInsignia/autotrain-Online_orders-755323156", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("xInsignia/autotrain-Online_orders-755323156", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```