When stripnet_freeze=False, all StripNet backbone params train end-to-end
with a separate optimizer group at lr * stripnet_backbone_lr_factor (default
0.1, so 1e-5 with default learning_rate=1e-4) — typical fine-tuning practice
for ImageNet-pretrained CNNs to avoid catastrophic forgetting.
Conv-MONA is now optional (stripnet_mona_last_n_stages=0 disables it). Three
modes are now supported:
- frozen + MONA: PEFT-style (~1.2M trainable, original default)
- unfrozen, no MONA: full fine-tune (~13.85M, all backbone params)
- unfrozen + MONA: hybrid (~14.5M, backbone + extra adapters)
_build_param_groups: new "backbone" group identifies image_encoder.backbone.*
params (excluding mona_*) when backbone="stripnet"; assigned lr factor
controls fine-tune step size independently from text/MONA groups.
conf/gtauav_balanced_stripnet_unfrozen.gin + baseline variant: ready-to-use
configs for full fine-tune experiment.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>