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Ma7ee7/Meet7_0.6b_Exp_Q4_K_M

🤗 On Hugging Facetext-generationapache-2.0397 MBGGUF✓ HF checksums availableupdated today
Magnet

Meet7 0.6B — Experimental

A continued fine-tune of Meet7 0.6B, trained at a lower learning rate on the same 600-sample dataset. Trades Meet7's sharp BoolQ spike for more balanced commonsense and reasoning gains across the board.

Benchmarks

0-shot evaluation, scores are acc_norm.

| Task | Qwen3-0.6B (Base) | Meet7 0.6B | Experimental | Δ vs Base |

|------|:-----------------:|:----------:|:------------:|:---------:|

| BoolQ | 0.3798 | 0.5554 | 0.3991 | +01.93% |

| ARC Easy | 0.3384 | 0.3952 | 0.3965 | +05.81% |

| ARC Challenge | 0.2841 | 0.3285 | 0.3259 | +04.18% |

| HellaSwag | 0.3981 | 0.4205 | 0.4265 | +02.84% |

| PIQA | 0.6338 | 0.6583 | 0.6687 | +03.49% |

| Winogrande | 0.5225 | 0.5201 | 0.5304 | +00.79% |

What these measure

  • BoolQ — Reading comprehension and yes/no factual grounding
  • ARC Easy / Challenge — Grade-school science reasoning; Challenge is the retrieval-resistant subset
  • HellaSwag — Commonsense sentence completion
  • PIQA — Physical world intuition
  • Winogrande — Commonsense pronoun resolution

vs Meet7 0.6B

This model is more balanced than Meet7. It outperforms Meet7 on HellaSwag, PIQA, and Winogrande — the physical and commonsense intuition tasks — at the cost of Meet7's large BoolQ advantage. If you need consistent commonsense reasoning, prefer this model. If yes/no QA is your primary use case, prefer Meet7.

Model Details

| | |

|---|---|

| Developed by | Ma7ee7 |

| License | Apache-2.0 |

| Base model | Ma7ee7/Meet7_0.6b |

| Original base | unsloth/Qwen3-0.6B-unsloth-bnb-4bit |

| Training samples | 600 |

| Training | Continued LoRA fine-tune, lower LR |

Trained 2x faster with Unsloth and Hugging Face TRL.

[](https://github.com/unslothai/unsloth)