Update README.md

README.md

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 ### Description
 
+Gemma 3 12B-IT LoRA Fine-tuned for LLM Training Expertise
+This model is a fine-tuned version of Google's Gemma 3 12B-IT, specialized in providing detailed and accurate information about LoRA (Low-Rank Adaptation) and fine-tuning techniques for large language models. The fine-tuning was performed using the sardor233/gemma3_12b-it_dataset which contains carefully curated instruction-response pairs focused on efficient model adaptation techniques.
+Model Description
+The base model (Gemma 3 12B-IT) has been fine-tuned using LoRA to specialize in explaining technical concepts and providing practical guidance related to LLM fine-tuning, with particular focus on parameter-efficient techniques.
+LoRA Configuration Used:
+
+Rank (r): 16
+Alpha: 32
+Target modules: q_proj, k_proj, v_proj, o_proj (attention layers)
+LoRA dropout: 0.05
+
+Capabilities
+This model excels at:
+
+Explaining technical concepts related to LoRA and other parameter-efficient fine-tuning methods
+Providing step-by-step implementation guidance for fine-tuning Gemma models
+Discussing hyperparameter selection and optimization strategies
+Comparing different fine-tuning approaches and their tradeoffs
+Recommending best practices for dataset preparation and model training
+
+Training Dataset
+The model was fine-tuned on the sardor233/gemma3_12b-it_dataset, which contains high-quality instruction-response pairs covering:
+
+Fundamental concepts of LoRA and fine-tuning
+Mathematical principles behind parameter-efficient techniques
+Implementation code examples and walkthroughs
+Hyperparameter selection and optimization
+Best practices for dataset preparation
+Troubleshooting common issues in model adaptation
+Comparative analysis of different fine-tuning methods
+
 Gemma is a family of lightweight, state-of-the-art open models from Google,
 built from the same research and technology used to create the Gemini models.
 Gemma 3 models are multimodal, handling text and image input and generating text