| tags: | |
| - pytorch | |
| - lightning | |
| - classification | |
| - time-series | |
| datasets: | |
| - uci-har | |
| metrics: | |
| - accuracy | |
| # SConvLSTM for UCI Human Activity Recognition | |
| This repository contains the training logs and checkpoints for a **SConvLSTM** model trained on the **UCI Human Activity Recognition (HAR)** dataset. | |
| ## Model Description | |
| The model is a hybrid **Convolutional Neural Network (CNN)** and **Long Short-Term Memory (LSTM)** network (SConvLSTM). | |
| - **Input**: 9 inertial signals (body acc x/y/z, body gyro x/y/z, total acc x/y/z). | |
| - **Architecture**: 3x 1D Conv layers (feature extraction) -> 2x LSTM layers (temporal modeling) -> Fully Connected layer. | |
| - **Task**: Multi-class classification (6 activities: Walking, Walking Upstairs, Walking Downstairs, Sitting, Standing, Laying). | |
| ## Training | |
| The model was trained using **PyTorch Lightning**. | |
| - **Optimizer**: AdamW | |
| - **Loss**: CrossEntropyLoss | |
| - **Hyperparameters**: | |
| - Batch size: 64 | |
| - Epochs: 20 | |
| - Learning Rates: Sweep [0.1, 0.01, ..., 1e-6] | |
| ## Results | |
| Check the TensorBoard logs in this repository for training and validation performance across different learning rates. | |