# Final Squeeze — Performance Push (full Toxic-BERT unfreeze, TTA, micro-LR anchor) pipeline: random_state: 42 test_size: 0.2 val_size: 0.15 max_train_test_gap: 0.048 # Gap defense budget (4.8 pp) target_f1_weighted: 0.80 data: raw_path: data/raw/youtoxic_english_1000.csv processed_preprocessed: data/processed/v2/comments_preprocessed.csv processed_stats: data/processed/v2/comments_with_stats.csv target_binary: IsToxic text_column: Text id_column: CommentId features_config: configs/features.yaml augmentation: enabled: true strategy: back_translation source_lang: en pivot_lang: de min_words: 3 max_words: 60 rate_limit_every: 50 rate_limit_sleep_sec: 1.0 dedup: enabled: true cosine_threshold: 0.95 embedding_model: sentence-transformers/all-MiniLM-L6-v2 transformer: model_id: unitary/toxic-bert max_length: 128 freeze_mode: full # all encoder layers + head (6 blocks in Toxic-BERT stack) learning_rate: 5.0e-6 weight_decay: 0.01 max_epochs: 20 batch_size: 8 warmup_ratio: 0.1 head_dropout: 0.3 label_smoothing: 0.1 early_stopping: patience: 4 metric: f1_weighted gap_stop_enabled: true max_train_val_gap: 0.048 gap_check_min_epoch: 2 metric_for_best: f1_weighted threshold_tuning: enabled: true metric: f1_weighted min_threshold: 0.30 max_threshold: 0.70 step: 0.01 test_time_augmentation: enabled: true source_lang: en pivot_lang: de max_words: 60 rate_limit_every: 50 rate_limit_sleep_sec: 1.0 logistic_regression: C: 0.01 max_iter: 2000 class_weight: balanced solver: lbfgs gap_search: enabled: true max_gap: 0.048 use_original_train_for_gap: true param_grid: - {C: 0.01, max_features: 300, min_df: 3} - {C: 0.008, max_features: 300, min_df: 5} - {C: 0.005, max_features: 300, min_df: 8} - {C: 0.01, max_features: 300, min_df: 5} tfidf: max_features: 300 ngram_range: [1, 2] sublinear_tf: true min_df: 3 ensemble: bert_weight: 0.95 lr_weight: 0.05 fixed_weights: true threshold_tuning: enabled: true metric: f1_weighted min_threshold: 0.30 max_threshold: 0.70 step: 0.01 output: transformer_dir: models/performance_push_toxic_bert lr_path: models/performance_push_lr.joblib ensemble_meta_path: models/performance_push_ensemble_meta.json reports_dir: reports/performance_push