AVA-v3-checkpoints / README.md
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---
license: apache-2.0
base_model: Qwen/Qwen3.5-4B
tags:
- code
- qlora
- checkpoint-fabric
- work-in-progress
---
# AVA v3 β€” Training Checkpoints (work in progress)
Training artifacts for **AVA v3.0**, a coding-specialist model built on a
$0 compute budget: free Colab/Kaggle GPU quota + one 4 GB-VRAM laptop, with
Hugging Face Hub as the single source of truth for resume-anywhere training.
**Recipe:** QLoRA (r=16, all-linear) on [Qwen/Qwen3.5-4B](https://huggingface.co/Qwen/Qwen3.5-4B)
(native 3:1 Gated DeltaNet hybrid, 262K ctx), trained on
nvidia/OpenCodeReasoning + bigcode/commitpackft (hash-anchored edit dialect),
completion-only loss, decontaminated against the eval sets below.
## Donor baseline (C1, the bar every checkpoint is gated against)
4-bit NF4, zero-shot, non-thinking, greedy β€” deployment-realistic protocol:
| Benchmark | Score |
|---|---|
| HumanEval+ (164, executed) | 67.68 |
| MBPP+ (378, executed) | 66.14 |
| ARC-Easy (floor >= 75) | 93.98 |
| MMLU (floor >= 45) | 55.50 |
## Repo layout
- `reports/c1_donor_baseline.json` β€” immutable baseline (per-task results)
- `reports/probes/` β€” mid-training probe evals (matched-subset deltas)
- `checkpoints/C5/` β€” live training state: adapters + optimizer + RNG +
data cursor; `LATEST.json` pointer written last (atomic resume)
- `wheels/` β€” cached causal-conv1d builds per platform tag
- `archive/` β€” forensic notes on reset runs
## Status
- C1 donor baseline: **done**
- C5 SFT: **run 2 in progress** (run 1 reset after a data-cursor bug was
caught by probe evals β€” see `archive/`)
- Gate: candidate must stay within 2pp of donor code scores and above the
sanity floors, evaluated by the same harness that set the baseline
Training pipeline, evals and the resumable-notebook autopilot live in the
[AVA repo](https://github.com/NAME0x0/AVA) under `experiments/exp6_v3/`.