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Commandline tools for training Fathom rulesets

Project description

This is the commandline trainer for Fathom, which itself is a supervised-learning system for recognizing parts of web pages. It also includes other commandline tools for ruleset development, like fathom-unzip, fathom-pick, and fathom-list. See docs for the trainer here.

Version History

  • Add fathom-list tool.
  • Further optimize trainer: about 17x faster for a 60-sample corpus, with superlinear improvements for larger ones.
  • Move to Fathom repo.
  • Add fathom-unzip and fathom-pick.
  • Switch to the Adam optimizer, which is significantly more turn-key, to the point where it doesn’t need its learning-rate decay set manually.
  • Tolerate pages for which no candidate nodes were collected.
  • Add 95% CI for per-page training accuracy.
  • Add validation-guided early stopping.
  • Revise per-page accuracy calculation and display.
  • Shuffle training samples before training.
  • Add false-positive and false-negative numbers to per-tag metrics.
  • First release, intended for use with Fathom itself 3.0 or later

Project details

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Files for fathom-web, version 3.1
Filename, size File type Python version Upload date Hashes
Filename, size fathom_web-3.1-py2.py3-none-any.whl (10.5 kB) File type Wheel Python version py2.py3 Upload date Hashes View hashes
Filename, size fathom-web-3.1.tar.gz (7.9 kB) File type Source Python version None Upload date Hashes View hashes

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