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AronDaron/Qwen2.5-Coder-7B-Instruct-DatasetGen-v2

sourceHugging Faceapache-2.0updated 5mo agoView on Hugging Face
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Model Card

Qwen2.5-Coder-7B-Instruct — Dataset Generator V2 Fine-tune

Fine-tuned version of Qwen2.5-Coder-7B-Instruct trained on Dataset Generator V2 — synthetic coding dataset generated with Dataset Generator.

Benchmark Results

ModelHumanEvalHumanEval+
Base Qwen2.5-Coder-7B-Instruct55.5% (±2.1)49.0% (±1.9)
This model (FT V2)60.0% (±0.9)54.0% (±1.8)

+4.5pp on HumanEval, +5.0pp on HumanEval+ vs base — error bars don't overlap, statistically significant improvement (5 runs averaged).

<img src="./benchmark-v2.png" alt="Benchmark" width="600">

Training

  • —Method: QLoRA fine-tuning via Unsloth
  • —Base model: Qwen2.5-Coder-7B-Instruct
  • —Dataset: Dataset Generator V2 (1,135 multi-turn examples)
  • —Hardware: RTX 4070 Ti 12GB
  • —Quantization: Q4KM GGUF (quantized by Unsloth)
  • —Chat template: ChatML (embedded in GGUF)
  • —Context length: 32,768 tokens
  • —Evaluation: 5 runs on HumanEval/HumanEval+ at temp 0.2

Training logs and exact hyperparameters were not preserved — this was an exploratory fine-tune.

Training Data

Trained on Dataset Generator V2 — 1,135 multi-turn conversations across 8 coding categories:

  • —Code Generation & Debugging
  • —API, DevOps & Infrastructure
  • —Architecture, Testing & Refactoring
  • —Terminal, CLI & Tooling
  • —Algorithms & Data Manipulation
  • —Data Processing & Transformation
  • —Code Reasoning & Review
  • —Practical Multi-step Problem Solving

See the dataset card for full details including generation models and methodology.

Limitations

  • —Optimized for algorithmic coding and reasoning — shows measurable improvement on HumanEval/HumanEval+
  • —Not optimized for library-heavy workflows (pandas, numpy, requests) — for those use cases, train on a dataset with library-focused categories using Dataset Generator
  • —Multi-turn conversational style — produces explanations alongside code

Support

If this helped you:

  • —Ko-fi: https://ko-fi.com/arondaron
  • —ETH: 0xA6910bDa2a89ee38cA42883e365BB2DdFba3C2A1
  • —BTC: bc1qamarkursch3x8399qaly4md32ck5xgthnr9jpl
  • —SOL: 797jTzFRm9dd4joHPqvUjryeXi5rPbMwG6Rqj3wJrgMt

License

Apache-2.0 — inherited from base model Qwen2.5-Coder-7B-Instruct.

Built with Dataset Generator.