Update README.md

README.md

@@ -1,51 +1,51 @@
 ---
-            license: apache-2.0
-            language:
-            - en
-            tags:
-            - text-to-sql
-            - code
-            - sql
-            - fine-tuned
-            - unsloth
-            - lora
-            base_model: Snowflake/Arctic-Text2SQL-R1-7B
-            ---
+license: apache-2.0
+language:
+- en
+tags:
+- text-to-sql
+- code
+- sql
+- fine-tuned
+- unsloth
+- lora
+base_model: Snowflake/Arctic-Text2SQL-R1-7B
+---
 
-            # Snowflake/Arctic-Text2SQL-R1-7B Fine-tuned for NL2SQL++ v8
+# Snowflake/Arctic-Text2SQL-R1-7B Fine-tuned for NL2SQL++ v8
 
-            This model is a fine-tuned version of [Snowflake/Arctic-Text2SQL-R1-7B](https://huggingface.co/Snowflake/Arctic-Text2SQL-R1-7B) on the NL2SQL++ v8 dataset with code-with-thought reasoning.
+This model is a fine-tuned version of [Snowflake/Arctic-Text2SQL-R1-7B](https://huggingface.co/Snowflake/Arctic-Text2SQL-R1-7B) on the NL2SQL++ v8 dataset with code-with-thought reasoning.
 
-            ## Model Details
+## Model Details
 
-            - **Base Model**: Snowflake/Arctic-Text2SQL-R1-7B
-            - **Task**: Text-to-SQL generation
-            - **Dataset**: NL2SQL++ v8 with code-with-thought reasoning
-            - **Fine-tuning Method**: LoRA (Low-Rank Adaptation) with Unsloth
-            - **Quantization**: 16-bit merged weights
-            - **Maximum Sequence Length**: 32768 tokens
-            - **Training Dataset Size**: 46344 examples
-            - **Validation Dataset Size**: 1986 examples
+- **Base Model**: Snowflake/Arctic-Text2SQL-R1-7B
+- **Task**: Text-to-SQL generation
+- **Dataset**: NL2SQL++ v8 with code-with-thought reasoning
+- **Fine-tuning Method**: LoRA (Low-Rank Adaptation) with Unsloth
+- **Quantization**: 16-bit merged weights
+- **Maximum Sequence Length**: 32768 tokens
+- **Training Dataset Size**: 46344 examples
+- **Validation Dataset Size**: 1986 examples
 
-            ## Training Configuration
+## Training Configuration
 
-            ### LoRA Parameters
-            - **LoRA Rank (r)**: 64
-            - **LoRA Alpha**: 128
-            - **Target Modules**: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
+### LoRA Parameters
+- **LoRA Rank (r)**: 64
+- **LoRA Alpha**: 128
+- **Target Modules**: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
 
-            ### Training Hyperparameters
-            - **Learning Rate**: 0.0002
-            - **Training Epochs**: 2
-            - **Max Steps**: N/A (using epochs)
-            - **Train Batch Size**: 64
-            - **Eval Batch Size**: 50
-            - **Gradient Accumulation Steps**: 2
-            - **Effective Batch Size**: 128
-            - **Warmup Steps**: 0
-            - **Warmup Ratio**: 0.1
-            - **Optimizer**: AdamW (torch)
-            - **Learning Rate Scheduler**: Cosine
-            - **Weight Decay**: 0.01
-            - **Max Gradient Norm**: 1.0
-            - **Seed**: 3407
+### Training Hyperparameters
+- **Learning Rate**: 0.0002
+- **Training Epochs**: 2
+- **Max Steps**: N/A (using epochs)
+- **Train Batch Size**: 64
+- **Eval Batch Size**: 50
+- **Gradient Accumulation Steps**: 2
+- **Effective Batch Size**: 128
+- **Warmup Steps**: 0
+- **Warmup Ratio**: 0.1
+- **Optimizer**: AdamW (torch)
+- **Learning Rate Scheduler**: Cosine
+- **Weight Decay**: 0.01
+- **Max Gradient Norm**: 1.0
+- **Seed**: 3407