readme: ---
  language: 
  - en
  thumbnail: https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4
  tags:
  - text-classification
  - go-emotion
  - pytorch
  license: apache-2.0
  datasets:
  - go_emotions
  metrics:
  - Accuracy
  ---
  # Bert-Base-Uncased-Go-Emotion
  
  ## Model description:
  
  ## Training Parameters:
  ```
  Num examples = 169208
  Num Epochs = 3
  Instantaneous batch size per device = 16
  Total train batch size (w. parallel, distributed & accumulation) = 16
  Gradient Accumulation steps = 1
  Total optimization steps = 31728
  ```
  
  ## TrainOutput:
  ```
  'train_loss': 0.12085497042373672, 
  ```
  
  ## Evalution Output:
  ```
   'eval_accuracy_thresh': 0.9614765048027039,
   'eval_loss': 0.1164659634232521
  ```
  
  ## Colab Notebook:
  [Notebook](https://github.com/bhadreshpsavani/UnderstandingNLP/blob/master/go_emotion_of_transformers_multilabel_text_classification_v2.ipynb)