search

rasbt / machine-learning-notes

Collection of useful machine learning codes and snippets (originally intended for my personal use)
BSD 3-Clause "New" or "Revised" License
782 stars 139 forks source link

vgg16-cifar10 - CUDA (laptop) - AMD K9 (Windows) #5

Closed jcp31 closed 2 years ago

jcp31 commented 2 years ago

I ran your script vgg16-cifar10 and got the following results (2 runs).

My machine is ASUS ROG Zephyrus Duo 15 SE (laptop):

First run: performance mode

torch 1.11.0+cu113 device cuda Files already downloaded and verified Using cache found in C:\Users\jcpou/.cache\torch\hub\pytorch_vision_v0.11.0 Epoch: 001/001 | Batch 0000/1406 | Loss: 2.3515 Epoch: 001/001 | Batch 0100/1406 | Loss: 2.2140 Epoch: 001/001 | Batch 0200/1406 | Loss: 2.3048 Epoch: 001/001 | Batch 0300/1406 | Loss: 2.2738 Epoch: 001/001 | Batch 0400/1406 | Loss: 2.3186 Epoch: 001/001 | Batch 0500/1406 | Loss: 1.8402 Epoch: 001/001 | Batch 0600/1406 | Loss: 1.8930 Epoch: 001/001 | Batch 0700/1406 | Loss: 2.4219 Epoch: 001/001 | Batch 0800/1406 | Loss: 1.8200 Epoch: 001/001 | Batch 0900/1406 | Loss: 1.8298 Epoch: 001/001 | Batch 1000/1406 | Loss: 1.8207 Epoch: 001/001 | Batch 1100/1406 | Loss: 1.8437 Epoch: 001/001 | Batch 1200/1406 | Loss: 1.4916 Epoch: 001/001 | Batch 1300/1406 | Loss: 1.6030 Epoch: 001/001 | Batch 1400/1406 | Loss: 1.9421 Time / epoch without evaluation: 7.04 min Epoch: 001/001 | Train: 38.71% | Validation: 38.70% | Best Validation (Ep. 001): 38.70% Time elapsed: 9.70 min Total Training Time: 9.70 min Test accuracy 39.42% Total Time: 10.25 min

Second run: turbo mode

torch 1.11.0+cu113 device cuda Files already downloaded and verified Using cache found in C:\Users\jcpou/.cache\torch\hub\pytorch_vision_v0.11.0 Epoch: 001/001 | Batch 0000/1406 | Loss: 2.4374 Epoch: 001/001 | Batch 0100/1406 | Loss: 2.2763 Epoch: 001/001 | Batch 0200/1406 | Loss: 2.1181 Epoch: 001/001 | Batch 0300/1406 | Loss: 2.1129 Epoch: 001/001 | Batch 0400/1406 | Loss: 2.0286 Epoch: 001/001 | Batch 0500/1406 | Loss: 2.2182 Epoch: 001/001 | Batch 0600/1406 | Loss: 1.8516 Epoch: 001/001 | Batch 0700/1406 | Loss: 2.0691 Epoch: 001/001 | Batch 0800/1406 | Loss: 1.8235 Epoch: 001/001 | Batch 0900/1406 | Loss: 1.9100 Epoch: 001/001 | Batch 1000/1406 | Loss: 1.7260 Epoch: 001/001 | Batch 1100/1406 | Loss: 1.9619 Epoch: 001/001 | Batch 1200/1406 | Loss: 1.7266 Epoch: 001/001 | Batch 1300/1406 | Loss: 1.8404 Epoch: 001/001 | Batch 1400/1406 | Loss: 2.2174 Time / epoch without evaluation: 6.66 min Epoch: 001/001 | Train: 34.86% | Validation: 35.98% | Best Validation (Ep. 001): 35.98% Time elapsed: 9.19 min Total Training Time: 9.19 min Test accuracy 35.99% Total Time: 9.71 min

rasbt commented 2 years ago

This is the same as #6 right? Closing just to keep things organized.

jcp31 commented 2 years ago

Network problem while I was posting the results => posting them twice

Le dim. 22 mai 2022, 16:31, Sebastian Raschka @.***> a écrit :

This is the same as #6 https://github.com/rasbt/machine-learning-notes/issues/6 right? Closing just to keep things organized.

— Reply to this email directly, view it on GitHub https://github.com/rasbt/machine-learning-notes/issues/5#issuecomment-1133909413, or unsubscribe https://github.com/notifications/unsubscribe-auth/AZITWCPDFFHTNXYB6IZAWI3VLJAMRANCNFSM5WSCN3TQ . You are receiving this because you authored the thread.Message ID: @.***>