metadata
license: other
library_name: pytorch
tags:
- emotion-recognition
- distillation
- efficientnet
- multitask
datasets:
- aussiegingersnap2/scroll-happy-emotion
metrics:
- spearmanr
model-index:
- name: v0.3e-bias-w1p5-seed-101
results:
- task:
type: image-classification
name: Soft-target Emotion Distillation
dataset:
name: scroll-happy-emotion (training_faces, val split)
type: aussiegingersnap2/scroll-happy-emotion
metrics:
- type: spearmanr
name: Mean row Spearman (emotions)
value: 0.7981
- type: spearmanr
name: Mean row Spearman (FACS)
value: 0.8919
- type: spearmanr
name: Mean row Spearman (descriptions)
value: 0.6896
- type: accuracy
name: Top-1 emotion vs teacher argmax
value: 0.3678
Scroll Happy Emotion — Student (efficientnet_b2)
EfficientNet student distilled from Hume teacher labels on
aussiegingersnap2/scroll-happy-emotion.
Predicts continuous probabilities for 48 emotions, 36 FACS AUs, and 27 facial descriptions from a single face crop.
Eval (held-out creators)
| Metric | Value |
|---|---|
| Mean row Spearman (emotions) | 0.7981 |
| Mean row Spearman (FACS) | 0.8919 |
| Mean row Spearman (descriptions) | 0.6896 |
| Top-1 emotion vs teacher | 0.3678 |
| Top-3 emotion recall vs teacher | 0.6356 |
| Dead emotion dims (val pred std < 1e-3) | 0/48 |
| Val rows | 15,896 |
Trackio run: v0.3e-bias-w1p5-seed-101 in project scroll-happy-emotion.