abrizu / abrizu/DementiaNet

reduce execution runtime

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#2 0 則留言 0 個 reaction 已指派 1 人 已被 @abrizu 認領 在 GitHub 檢視
bug
主要語言
Jupyter Notebook
星號
2
分支
0
PR 合併指標
30 天內沒有已合併 PR

描述

attempt to reduce the runtime of the mri model while maintaining optimal epoch count (5-10).

current runtime (Nvidia GTX 1080): 5.02 minutes @ 99.70% accuracy (3 epochs)
(high accuracy, runtime slow)

this may include:
- applying techniques such as dropout and batch norm effectively (currently implemented, may not be the best functionality)
- changing architecture

貢獻指南

這個儲存庫沒有索引到貢獻指南

研究方向

Examine the MRI model architecture in the repository, likely in a Jupyter Notebook. Look for the training loop and model definition to understand current dropout and batch norm usage. Benchmark runtime with the provided hardware spec, then experiment with architectural changes or hyperparameter tuning to reduce time while keeping accuracy above 99% over 5-10 epochs.

由索引模型根據 Issue 內容生成。

評估

技術堆疊
jupyter-notebook, python, pytorch, tensorflow
領域
machine-learning, performance
Issue 類型
重構
難度
4/5
預估耗時
3-5 天
活躍度
停滯
描述清晰度
基本清楚
新手友好度
35/100

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