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LLMs-from-scratch/ch05/05_bonus_hparam_tuning
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Daniel Kleine dcbdc1d2e5
fixes for code (#206) 
* updated .gitignore

* removed unused GELU import

* fixed model_configs, fixed all tensors on same device

* removed unused tiktoken

* update

* update hparam search

* remove redundant tokenizer argument

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Co-authored-by: rasbt <mail@sebastianraschka.com>
2024-06-11 20:59:48 -05:00
..
hparam_search.py
fixes for code (#206)
2024-06-11 20:59:48 -05:00
previous_chapters.py
fixes for code (#206)
2024-06-11 20:59:48 -05:00
README.md
Organized setup instructions (#115)
2024-04-10 22:09:46 -04:00
the-verdict.txt
Add and link bonus material (#84)
2024-03-23 07:27:43 -05:00

README.md

Optimizing Hyperparameters for Pretraining

The hparam_search.py script, based on the extended training function in Appendix D: Adding Bells and Whistles to the Training Loop, is designed to find optimal hyperparameters via grid search.

Note

This script will take a long time to run. You may want to reduce the number of hyperparameter configurations explored in the HPARAM_GRID dictionary at the top.