Update README.md

README.md

@@ -25,10 +25,41 @@ You can plug it into your calling or voice AI stack to automatically extract:
 
 It’s built to handle real-world Hindi, English, and mixed Hinglish calls, including noisy transcripts.
 
+Finetuning Parameters:
+```
+rank = 64
+lora_alpha = rank*2,
+target_modules = ["q_proj", "k_proj", "v_proj", "o_proj",
+                      "gate_proj", "up_proj", "down_proj",],
+SFTConfig(
+        dataset_text_field = "prompt",
+        per_device_train_batch_size = 32,
+        gradient_accumulation_steps = 1, # Use GA to mimic batch size!
+        warmup_steps = 5,
+        num_train_epochs = 2,
+        learning_rate = 2e-4,
+        logging_steps = 50,
+        optim = "adamw_8bit",
+        weight_decay = 0.001,
+        lr_scheduler_type = "linear",
+        seed = SEED,
+        report_to = "wandb",
+        eval_strategy="steps",
+        eval_steps=200,
+    )
+The model was finetuned on ~100,000 curated transcripts across different domanins and language preferences
+```
+![Training Overview](metrics.png)
 
 - **Developed by:** RinggAI
 - **License:** apache-2.0
 - **Finetuned from model :** unsloth/Qwen2.5-1.5B-Instruct
+- Parameter decision where made using 
+  **Schulman, J., & Thinking Machines Lab. (2025).**  
+  *LoRA Without Regret.*  
+  Thinking Machines Lab: Connectionism.  
+  DOI: 10.64434/tml.20250929  
+  Link: https://thinkingmachines.ai/blog/lora/