Log hyper-parameters, metric curves, and model state for deeplabv3plus-1024_run_2026-06-27_15-02

.gitattributes

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README.md

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+---
+language: en
+license: mit
+tags:
+- semantic-segmentation
+- pytorch
+- deeplabv3plus
+- resnet34
+- agricultural-cv
+model-index:
+- name: deeplabv3plus-1024_run_2026-06-27_15-02
+  results:
+  - task:
+      type: semantic-segmentation
+      name: Corm Segmentation
+    metrics:
+    - type: mean_iou
+      value: 0.9413518003361036
+      name: Best Val Mean IoU
+    - type: damage_iou
+      value: 0.8581994876991125
+      name: Best Val Damage-Class IoU
+    - type: corm_iou
+      value: 0.9676700661101357
+      name: Best Val Corm-Class IoU
+---
+
+# DeepLabV3+ Corm & Damage Semantic Segmentation Model
+
+This repository contains weights, performance curves, and hyperparameter logs for experiment `deeplabv3plus-1024_run_2026-06-27_15-02`.
+
+## Model Summary
+- **Architecture Type:** DeepLabV3+ (SMP wrapper)
+- **Backbone Encoder:** `resnet34`
+- **Pretrained Weights:** `imagenet`
+- **Input Channels:** 3
+- **Number of Classes:** 3 (0: background, 1: damage, 2: corm)
+- **Training Resolution:** `1024x1024`
+- **Loss Optimizer configuration:** `CrossEntropy`
+
+## Metrics Curves
+Below are the training performance plots generated for this run:
+![Performance Curves](performance_curves.png)

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config.json

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+    "encoder_name": "resnet34",
+    "encoder_weights": "imagenet",
+    "in_channels": 3,
+    "classes": 3,
+    "input_resolution": "1024x1024",
+    "loss_type": "CrossEntropy"
+}

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