Tune ANIMA LoRA defaults for batch 4 showcase validation

configs/ANIMA.knf.yaml

@@ -201,6 +201,10 @@ training:
         negative_control_species: wolf
         exchanges:
           - [erection, fully_sheathed]
+      from_prompt_pack:
+        prompts: rook-kaefer
+        caption_styles: [nlg]
+        uses: [training_validation]
 
     # Model and LoRA settings merged into the top-level SimpleTuner config.
     model:
@@ -250,7 +254,7 @@ training:
       hub_model_id: ladybird-anima-lora             # Optional Hub model id if push_to_hub is enabled.
 
       optimizer: adamw_bf16        # BF16 AdamW optimizer.
-      learning_rate: 0.00006        # Conservative Anima LoRA starting point.
+      learning_rate: 0.00008        # 
       lr_scheduler: constant_with_warmup # ramp up LR to avoid weird color biases.
       lr_warmup_steps: 100
       seed: 42                     # Training seed.
@@ -258,7 +262,7 @@ training:
       max_grad_norm: 1.0           # Clip gradients for stability.
       grad_clip_method: norm       # Clip by gradient norm.
 
-      train_batch_size: 2            # Per-device batch size.
+      train_batch_size: 4            # Per-device batch size.
       gradient_accumulation_steps: 1 # Effective batch multiplier.
       num_train_epochs: 0            # Step-based training; max_train_steps controls run length.
       max_train_steps: 1600          # Extended Anima character run with multi-subset curriculum.
@@ -269,7 +273,7 @@ training:
 
       # push_to_hub: false             # Upload final artifacts to Hugging Face Hub.
       # push_checkpoints_to_hub: false # Upload intermediate checkpoints.
-      checkpoints_total_limit: 5       # Keep latest 5 checkpoints.
+      checkpoints_total_limit: 4       # Keep latest 5 checkpoints.
       checkpoint_step_interval: 200    # Save checkpoint every 200 steps.
       validation_step_interval: 200    # Run validation every 200 steps.
       validation_on_startup: true      # Render baseline validation before training.