Snowflake/Arctic-Text2SQL-R1-7B Fine-tuned for NL2SQL++ v8

This model is a fine-tuned version of Snowflake/Arctic-Text2SQL-R1-7B on the NL2SQL++ v8 dataset with code-with-thought reasoning.

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

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

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
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