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cam_high + cam_left_wrist + cam_right_wrist.[3, 544, 320], CHW.[0, 255] or float [0, 1]; the model preprocessing converts to float [0, 1] and applies ImageNet normalization.full_weights.pt is a PyTorch state_dict for the RLinf-compatible ResNet18 binary reward model.stage1 has been completed.sigmoid(logit) is the stage1 completion probability.sigmoid(logit) >= 0.499094.| 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. |
| score | threshold | F1 | precision | recall | accuracy | TP | FP | TN | FN |
|---|---|---|---|---|---|---|---|---|---|
| probability | 0.499094 | 0.904943 | 0.832168 | 0.991667 | 0.895833 | 119 | 24 | 96 | 1 |
| logit | -0.003625 | 0.904943 | 0.832168 | 0.991667 | 0.895833 | 119 | 24 | 96 | 1 |
| split | samples | positives | negatives | loss | AUC | accuracy@prob0.5 | F1@prob0.5 | positive prob mean | negative prob mean |
|---|---|---|---|---|---|---|---|---|---|
| val | 240 | 120 | 120 | 0.601936 | 0.914722 | 0.891667 | 0.900763 | 0.971991 | 0.202400 |