bwsk-efficientnet-b0

tzervas/bwsk-efficientnet-b0

bwsk-efficientnet-b0 is a image classification model from tzervas. Use it when you need a label for an image. The card lists the license as mit.

EfficientNet-B0 (5M params) trained in 6 variants (3 BWSK modes x 2 experiments) on CIFAR-10 with full convergence training and early stopping.

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Public

Updated Mar 5, 2026

Repo size

98.2 MB

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Public

Hugging Face

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At a glance

Task: Image Classification
License: mit
Access: Public
Created: Mar 5, 2026
Updated: Mar 5, 2026
SHA: 13c6886d

Base models

google/efficientnet-b0

Datasets

cifar10

Model card

From the Hugging Face model README

BWSK EfficientNet-B0

EfficientNet-B0 (5M params) trained in 6 variants (3 BWSK modes x 2 experiments) on CIFAR-10 with full convergence training and early stopping.

This repo contains all model weights, configs, and training results in a single consolidated repository.

What is BWSK?

BWSK is a framework that classifies every neural network operation as S-type (information-preserving, reversible, coordination-free) or K-type (information-erasing, synchronization point) using combinator logic. This classification enables reversible backpropagation through S-phases to save memory, and CALM-based parallelism analysis.

Model Overview

Property	Value
Base Model	google/efficientnet-b0
Architecture	Cnn (image_cls)
Parameters	5M
Dataset	CIFAR-10
Eval Metric	Accuracy

S/K Classification

Type	Ratio
S-type (information-preserving)	33.5%
K-type (information-erasing)	59.6%
Gray (context-dependent)	7.0%

Fine-tune Results

Mode	Final Loss	Val Accuracy	Test Accuracy	Peak Memory	Time	Epochs
Conventional	0.3806	89.0%	89.6%	2.8 GB	57s	2
BWSK Analyzed	0.2952	89.3%	88.5%	2.8 GB	58s	2
BWSK Reversible	0.2530	90.1%	90.0%	2.8 GB	57s	2

Memory savings (reversible vs conventional): 0.0%

From Scratch Results

Mode	Final Loss	Val Accuracy	Test Accuracy	Peak Memory	Time	Epochs
Conventional	0.2993	87.4%	87.4%	2.8 GB	9.0m	10
BWSK Analyzed	0.5080	79.4%	78.8%	2.8 GB	4.8m	6
BWSK Reversible	0.3454	88.1%	87.1%	2.8 GB	8.9m	10