metadata
language: en
license: mit
tags:
- semantic-segmentation
- pytorch
- unet
- resnet34
- agricultural-cv
model-index:
- name: unet_run_2026-06-23_13-16
results:
- task:
type: semantic-segmentation
name: Corm Segmentation
metrics:
- type: mean_iou
value: 0.9293187884547999
name: Best Val Mean IoU
- type: mean_accuracy
value: 0.9665135754918103
name: Best Val Mean Accuracy
UNet Corm & Damage Semantic Segmentation Model
This repository contains the weights, performance logs, and hyperparameters for experiment unet_run_2026-06-23_13-16.
Model Hyperparameters
- Architecture Type: UNet (SMP wrapper)
- Backbone Encoder:
UNet - Pretrained Weights:
imagenet - Input Channels: 3
- Number of Classes: 3 (0: background, 1: damage, 2: root)
- Training Resolution:
256x256
Training Configurations
- Batch Size: 8
- Optimizers / Lr: AdamW / 0.0001
- Maximum Epochs: 200
- Seed Configuration: 42
Metrics Curves
Below are the training performance plots generated for this run:
