|
||||||||
Impact of Corpus Narrowness on Language Model Training - Python Automation and Machine Learning for ICs - - An Online Book - |
||||||||
Python Automation and Machine Learning for ICs http://www.globalsino.com/ICs/ | ||||||||
Chapter/Index: Introduction | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | Appendix | ||||||||
================================================================================= When training a language model with an overly narrow corpus, the probabilities are more likely to:
Using a diverse and representative corpus helps to mitigate these issues by ensuring that the language model learns a broad range of language patterns and contexts, enabling it to better reflect the task at hand, generalize to new situations, and provide more intuitive and accurate predictions.
============================================
|
||||||||
================================================================================= | ||||||||
|
||||||||