readme: ---
  tags: autotrain
  language: en
  widget:
  - text: "I love AutoTrain 🤗"
  datasets:
  - charly/autotrain-data-sentiment-4
  co2_eq_emissions: 0.007597570744740809
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 812425472
  - CO2 Emissions (in grams): 0.007597570744740809
  
  ## Validation Metrics
  
  - Loss: 0.5105093121528625
  - Accuracy: 0.8268156424581006
  - Macro F1: 0.6020923520923521
  - Micro F1: 0.8268156424581006
  - Weighted F1: 0.8021395116367184
  - Macro Precision: 0.5907986111111111
  - Micro Precision: 0.8268156424581006
  - Weighted Precision: 0.7792248603351954
  - Macro Recall: 0.6141625496464206
  - Micro Recall: 0.8268156424581006
  - Weighted Recall: 0.8268156424581006
  
  
  ## 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/charly/autotrain-sentiment-4-812425472
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("charly/autotrain-sentiment-4-812425472", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("charly/autotrain-sentiment-4-812425472", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```