readme: ---
  tags: autotrain
  language: en
  widget:
  - text: "I love AutoTrain 🤗"
  datasets:
  - agnihotri/autotrain-data-contract_type
  co2_eq_emissions: 0.07610944071640048
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 809725368
  - CO2 Emissions (in grams): 0.07610944071640048
  
  ## Validation Metrics
  
  - Loss: 0.05312908813357353
  - Accuracy: 0.9911504424778761
  - Macro F1: 0.9912087912087912
  - Micro F1: 0.9911504424778761
  - Weighted F1: 0.9908586988233007
  - Macro Precision: 0.9942857142857143
  - Micro Precision: 0.9911504424778761
  - Weighted Precision: 0.9924146649810366
  - Macro Recall: 0.99
  - Micro Recall: 0.9911504424778761
  - Weighted Recall: 0.9911504424778761
  
  
  ## 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/agnihotri/autotrain-contract_type-809725368
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("agnihotri/autotrain-contract_type-809725368", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("agnihotri/autotrain-contract_type-809725368", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```