| | ---
|
| | license: cc-by-4.0
|
| | tags:
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| | - pytorch
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| | - tornado-detection
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| | - weather
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| | - radar
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| | - nexrad
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| | - 3d-cnn
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| | - video-classification
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| | - severe-weather
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| | - dual-pol
|
| | datasets:
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| | - deepguess/tornet-temporal
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| | pipeline_tag: video-classification
|
| | ---
|
| |
|
| | # ResNet3D-34 for Tornado Detection
|
| |
|
| | A larger 3D CNN variant trained on temporal dual-polarimetric NEXRAD radar sequences. This is the **64M parameter** version -- see [resnet3d-18-tornet](https://huggingface.co/deepguess/resnet3d-18-tornet) for the smaller, equally performant 33M version.
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| |
|
| | ## Model Description
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| |
|
| | Same dual-head architecture as ResNet3D-18 but with deeper residual blocks (layers=[3,4,6,3]).
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| |
|
| | | Parameter | Value |
|
| | |-----------|-------|
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| | | Backbone | ResNet3D-34 (BasicBlock, layers=[3,4,6,3]) |
|
| | | Parameters | 63.7M |
|
| | | Input shape | (B, 24, 8, 128, 128) |
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| | | Output shape | (B, 4) |
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| |
|
| | ## Performance
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| |
|
| | ### Test Set (3,685 events)
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| |
|
| | | Head | AUC | CSI | F1 | Precision | Recall |
|
| | |------|-----|-----|-----|-----------|--------|
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| | | Detection | 0.898 | 0.540 | 0.701 | 0.596 | 0.851 |
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| | | Prediction | 0.988 | 0.865 | 0.928 | 0.924 | 0.932 |
|
| | | **Combined** | **0.943** | -- | -- | -- | -- |
|
| |
|
| | ### Key Finding
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| |
|
| | ResNet3D-34 (64M params) performs **nearly identically** to ResNet3D-18 (33M params) on this task (combined AUC 0.943 vs 0.942). The smaller model is recommended for deployment due to faster inference and lower memory usage.
|
| |
|
| | ## Training
|
| |
|
| | | Parameter | Value |
|
| | |-----------|-------|
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| | | Optimizer | AdamW (lr=1e-3) |
|
| | | Batch size | 512 |
|
| | | Epochs | 20 |
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| | | GPU | NVIDIA H200 (144GB) |
|
| |
|
| | ## Usage
|
| |
|
| | Same as ResNet3D-18 -- see [resnet3d-18-tornet](https://huggingface.co/deepguess/resnet3d-18-tornet) for full usage instructions and deployment guidance.
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| |
|
| | ```python
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| | from model_resnet3d import DualHeadResNet3D
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| | model = DualHeadResNet3D(in_channels=24, arch="resnet34")
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| | state = torch.load("best.pt", map_location="cpu")
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| | model.load_state_dict(state["model_state_dict"])
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| | ```
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| |
|
| | ## Citation
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| |
|
| | ```bibtex
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| | @model{resnet3d-34-tornet,
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| | title={ResNet3D-34 for Temporal Radar Tornado Detection},
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| | author={DeepGuess},
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| | year={2026},
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| | url={https://huggingface.co/deepguess/resnet3d-34-tornet},
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| | }
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| | ```
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| |
|
