readme: ---
  language: 
  - en
  thumbnail: https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4
  tags:
  - text-classification
  - emotion
  - pytorch
  license: apache-2.0
  datasets:
  - emotion
  metrics:
  - accuracy
  ---
  
  # bert-base-uncased-emotion
  
  ## Model description
  
  `bert-base-uncased` finetuned on the emotion dataset using PyTorch Lightning. Sequence length 128, learning rate 2e-5, batch size 32, 2 GPUs, 4 epochs.
  
  For more details, please see, [the emotion dataset on nlp viewer](https://huggingface.co/nlp/viewer/?dataset=emotion).
  
  
  #### Limitations and bias
  
  - Not the best model, but it works in a pinch I guess...
  - Code not available as I just hacked this together.
  - [Follow me on github](https://github.com/nateraw) to get notified when code is made available.
  
  ## Training data
  
  Data came from HuggingFace's `datasets` package. The data can be viewed [on nlp viewer](https://huggingface.co/nlp/viewer/?dataset=emotion).
  
  
  ## Training procedure
  ...
  
  ## Eval results
  
  val_acc - 0.931 (useless, as this should be precision/recall/f1)
  
  The score was calculated using PyTorch Lightning metrics.
  