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insert-mouse-battery-stage1-resnet18-reward-v1
qmddn/insert-mouse-battery-stage1-resnet18-reward-v1
insert-mouse-battery-stage1-resnet18-reward-v1 is a machine learning model from qmddn. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
- RGB three-view vertical stack in Wan world-model format. - View order: camhigh + camleftwrist + camrightwrist. - Tensor shape: [3, 544, 320], CHW. - Accepted value range: uint8 [0, 255] or float [0, 1]; the model pr…
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Updated Jun 12, 2026
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.pt45.3 MB · 100%
At a glance
- Access
- Public
- Created
- Jun 12, 2026
- Updated
- Jun 12, 2026
- SHA
- c54faa36
Model card
From the Hugging Face model README
insert-mouse-battery Stage1 ResNet18 Reward
Input Format
- RGB three-view vertical stack in Wan world-model format.
- View order:
cam_high + cam_left_wrist + cam_right_wrist. - Tensor shape:
[3, 544, 320], CHW. - Accepted value range: uint8
[0, 255]or float[0, 1]; the model preprocessing converts to float[0, 1]and applies ImageNet normalization.
Output Format
full_weights.ptis a PyTorch state_dict for the RLinf-compatible ResNet18 binary reward model.- The model returns one raw scalar logit for whether
stage1has been completed. sigmoid(logit)is the stage1 completion probability.- Recommended inference rule: positive when
sigmoid(logit) >= 0.127747.
Files
| File | Description |
|---|---|
full_weights.pt | ResNet18 stage1 reward checkpoint. |
model_metadata.json | Input/output schema, dataset counts, and model metadata. |
eval_summary.json | Validation metrics and F1 threshold sweep result. |
README.md | This model card. |
F1 Threshold
| score | threshold | F1 | precision | recall | accuracy | TP | FP | TN | FN |
|---|---|---|---|---|---|---|---|---|---|
| probability | 0.127747 | 0.935065 | 0.878049 | 1.000000 | 0.930556 | 36 | 5 | 31 | 0 |
| logit | -1.921025 | 0.935065 | 0.878049 | 1.000000 | 0.930556 | 36 | 5 | 31 | 0 |
Validation Results
| split | samples | positives | negatives | loss | AUC | [email protected] | [email protected] | positive prob mean | negative prob mean |
|---|---|---|---|---|---|---|---|---|---|
| val | 72 | 36 | 36 | 0.242218 | 0.966821 | 0.916667 | 0.914286 | 0.797100 | 0.097980 |
- Created
- Jun 12, 2026
- Updated
- Jun 12, 2026