Purpose
Train a bounded, traceable EvoStream adapter on top of the accepted Nano
scaffold using verified donor, code, reasoning, safety, and Omni contracts.
Result
- Training status:
OK
- Loss before:
2.59765
- Loss after:
2.559422
- Train losses:
[1.429411, 2.185695, 1.758911, 3.044919, 1.152849, 1.433145, 0.960366, 0.732565, 1.325378, 2.308462, 2.535948, 1.287751, 1.272575, 1.609289, 4.81366, 1.082453, 4.178133, 4.02433, 4.390209, 4.39222, 3.61718, 2.580169, 3.106896, 3.954231, 3.766961, 1.590856, 3.03544, 2.990237, 3.60154, 3.90493, 4.112782, 0.776599, 1.386399, 2.127077, 1.716018, 3.047485]
- Trainable parameters:
110484224
- Trainable ratio:
0.00348658
- Train JSONL path:
/workspace/gamma_30b_alpha_lora/input/gamma30_v2_4_1_qwen36_compact_repair_pack_20260615.jsonl
- Train items:
32
Next
Run strict v2.1 evaluation, then merge/unload or consolidate only if accepted.