Phil 9.18.21

WeightWatcher (WW): is an open-source, diagnostic tool for analyzing Deep Neural Networks (DNN), without needing access to training or even test data. It can be used to:

  • analyze pre/trained pyTorch, Keras, DNN models (Conv2D and Dense layers)
  • monitor models, and the model layers, to see if they are over-trained or over-parameterized
  • predict test accuracies across different models, with or without training data
  • detect potential problems when compressing or fine-tuning pretrained models
  • layer warning labels: over-trained; under-trained

GPT Agents

  • Finished extracting French, Chinese and Mexican reviews and ran the sentiment analyzer
  • Finished creating the French, Chinese, and Mexican models (50k reviews, 6 epochs). Need to run them next
  • I want to try WW (above) on the stars models and see what it says