readme: ---
  license: apache-2.0
  ---
  
  Number of Epochs = 5 <br>
  Dataset Size = 5.5 k samples [train/validation] <br>
  Number of labels used = 2 <br>
  Thresholding = True<br>
  Thresholding value = 0.7<br>
  
  Below is the function to aplly thresholding to output logits.
  
  
  ```python
    def get_prediction(text):
      encoding = tokenizer(text, return_tensors="pt", padding="max_length", truncation=True, max_length=128)
      encoding = {k: v.to(trainer.model.device) for k,v in encoding.items()}
  
      outputs = model(**encoding)
  
      logits = outputs.logits
  
      sigmoid = torch.nn.Sigmoid()
      probs = sigmoid(logits.squeeze().cpu())
      probs = probs.detach().numpy()
      label = np.argmax(probs, axis=-1)
      if label == 1:
          if probs[1] > 0.7:
              return 1
          else:
              return 0
      else:
          return 0
  ```