readme: ---
  tags: autotrain
  language: unk
  widget:
  - text: "Climate Change is a hoax"
  - text: "It is freezing, where is global warming"
  datasets:
  - KeithHorgan98/autotrain-data-TweetClimateAnalysis
  co2_eq_emissions: 133.19491276284793
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 678720226
  - CO2 Emissions (in grams): 133.19491276284793
  
  ## Validation Metrics
  
  - Loss: 0.4864234924316406
  - Accuracy: 0.865424430641822
  - Macro F1: 0.7665472174344069
  - Micro F1: 0.8654244306418221
  - Weighted F1: 0.8586375445115083
  - Macro Precision: 0.8281449061702826
  - Micro Precision: 0.865424430641822
  - Weighted Precision: 0.8619727477790186
  - Macro Recall: 0.736576343905098
  - Micro Recall: 0.865424430641822
  - Weighted Recall: 0.865424430641822
  
  
  ## 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/KeithHorgan98/autotrain-TweetClimateAnalysis-678720226
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("KeithHorgan98/autotrain-TweetClimateAnalysis-678720226", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("KeithHorgan98/autotrain-TweetClimateAnalysis-678720226", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```