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f211247 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | # EfficientNetV2-M sınıflandırıcı eğitim parametreleri
# Referans: arXiv 2505.04678 — EfficientNetV2M, 99.99% top-1 (235 sınıf, 14K veri)
# Tan & Le (2021) — EfficientNetV2: Smaller Models and Faster Training
model_name: tf_efficientnetv2_m
epochs: 120
batch: 32 # GPU başına (V2M daha büyük → batch küçültüldü)
lr: 0.0003 # Daha düşük LR — büyük model
img_size: 224 # EfficientNetV2-M native çözünürlük
patience: 30
device: 0
workers: 10
name: hitit_cls_effnetv2m
# Loss
loss: focal
label_smoothing: 0.1
focal_gamma: 2.0
focal_alpha: 1.0
# Augmentation
mixup: true
mixup_alpha: 0.2
tailmix: true
tailmix_threshold: 50
cutmix: true
# Scheduler
scheduler: cosine_warm_restarts
T_0: 20
T_mult: 2
eta_min: 0.000001
# Sınıf dengesizliği
use_weighted_sampler: true
class_weight_method: effective_num
# EfficientNet-specific
efficientnet:
drop_rate: 0.3
drop_path_rate: 0.2
layerwise_lr_decay: 0.85 # Katman bazlı LR decay — alt katmanlar düşük LR alır
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