readme: ---
  tags: autotrain
  language: fr
  widget:
  - text: "I love AutoTrain 🤗"
  datasets:
  - ziedhajyahia/autotrain-data-ok
  co2_eq_emissions: 5.096755166899446
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 848227025
  - CO2 Emissions (in grams): 5.096755166899446
  
  ## Validation Metrics
  
  - Loss: 2.1917402744293213
  - Accuracy: 0.44666666666666666
  - Macro F1: 0.20291677804725128
  - Micro F1: 0.44666666666666666
  - Weighted F1: 0.37709801275435956
  - Macro Precision: 0.19919016697588127
  - Micro Precision: 0.44666666666666666
  - Weighted Precision: 0.3478004329004329
  - Macro Recall: 0.23167713239141807
  - Micro Recall: 0.44666666666666666
  - Weighted Recall: 0.44666666666666666
  
  
  ## 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/ziedhajyahia/autotrain-ok-848227025
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("ziedhajyahia/autotrain-ok-848227025", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("ziedhajyahia/autotrain-ok-848227025", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```