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code/train_sft.py

@@ -54,7 +54,7 @@ from config import ViuAIConfig, ModelArgs
 
 PAD_TOKEN_ID = 64000
 
-DOMAIN_NAMES = {
+DOMAIN_NAMES_V18 = {
     0: "gk_polity_history",
     1: "coding_tech",
     2: "math_logic",
@@ -67,6 +67,26 @@ DOMAIN_NAMES = {
     9: "identity_greetings"
 }
 
+DOMAIN_NAMES_V19 = {
+    0: "identity_greetings",
+    1: "coding_tech",
+    2: "math_logic",
+    3: "reasoning_domain",
+    4: "empathetic_chitchat",
+    5: "career_productivity",
+    6: "recipes_indian_utility",
+    7: "finance_health_wellness",
+    8: "translation_multilingual",
+    9: "gk_polity_history",
+    10: "multiturn_conversations",
+    11: "typo_robustness",
+    12: "hinglish_codemixed",
+    13: "safety_refusal",
+    14: "instruction_following"
+}
+
+DOMAIN_NAMES = DOMAIN_NAMES_V19
+
 
 # ------------------------------------------------------------------------------
 # 1. Universal Hardware Prober & Auto-Tuner
@@ -350,6 +370,12 @@ def main():
         except Exception:
             pass
 
+    global DOMAIN_NAMES
+    if "19" in str(args.version).lower():
+        DOMAIN_NAMES = DOMAIN_NAMES_V19
+    else:
+        DOMAIN_NAMES = DOMAIN_NAMES_V18
+
     device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
     if torch.cuda.is_available():
         torch.cuda.empty_cache()
@@ -358,6 +384,7 @@ def main():
     print(f"🚀 ViuAI Sarus-500M — SFT {args.version.upper()} Ultra-Optimized Master Training Engine")
     print(f"   • Hardware Tier:     {hw['tier']} ({hw['desc']})")
     print(f"   • Device Name:       {hw['device_name']} | Total VRAM: {hw['vram_gb']:.2f} GB")
+    print(f"   • Active Domains:    {len(DOMAIN_NAMES)} domains tracked during evaluation")
     print(f"   • Auto-Tuned Batch:  Micro-Batch {micro_b} × Grad-Accum {grad_acc} = Effective Batch {eff_batch}")
     print(f"   • NEFTune Noise:     alpha = {args.neftune_alpha} (Noisy Embedding Fine-Tuning Active)")
     print(f"   • Length Grouping:   Active (LengthGroupedBatchSampler - ~50% padding saved)")