readme: ---
  tags: autotrain
  language: en
  widget:
  - text: "I love AutoTrain 🤗"
  datasets:
  - intellisr/autotrain-data-twitterMbti
  co2_eq_emissions: 0.3313142450338848
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 758223271
  - CO2 Emissions (in grams): 0.3313142450338848
  
  ## Validation Metrics
  
  - Loss: 1.2496932744979858
  - Accuracy: 0.6438828259620908
  - Macro F1: 0.5757131072506373
  - Micro F1: 0.6438828259620908
  - Weighted F1: 0.6401462906378685
  - Macro Precision: 0.6279826743318115
  - Micro Precision: 0.6438828259620908
  - Weighted Precision: 0.6479595607607238
  - Macro Recall: 0.5436771609966322
  - Micro Recall: 0.6438828259620908
  - Weighted Recall: 0.6438828259620908
  
  
  ## 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/intellisr/autotrain-twitterMbti-758223271
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("intellisr/autotrain-twitterMbti-758223271", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("intellisr/autotrain-twitterMbti-758223271", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```