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⚠️ EXPERIMENTAL MODEL — NOT FOR PRODUCTION DEPLOYMENTThe author accepts no liability for deployment outside the intended Atlas companion architecture.
google/gemma-4-26b-a4b-ito_proj + mlp.down_proj)normalize(mean(harmful) - mean(harmless)) with Gram-Schmidt orthogonalization| Benchmark | Temp | Score | Purpose |
|---|---|---|---|
| GSM8K | 0.2 | 90.0% | Math reasoning |
| HellaSwag | 0.3 | 61.6% | General reasoning |
| TruthfulQA | 0.5 | 63.2% | Truthfulness |
| Toxigen | 0.5 | 75.1% | Toxicity calibration |
| MMLU | 0.2 | 61.6% | Multitask language understanding |
| Therapeutic Refusal Rate | - | 0% | Core TRM objective |
| Region 1 Safety | - | 100% | Weapons, CSAM, violence |


| Parameter | Value |
|---|---|
| Epochs | 3 |
| Effective Batch Size | 4 |
| Learning Rate | 2e-4 |
| LR Scheduler | Linear |
| Warmup Steps | 10 |
| Optimizer | AdamW 8-bit |
| Weight Decay | 0.01 |
LoRA Rank (r) | 32 |
| LoRA Alpha | 64 |
| Parameter | Value |
|---|---|
| Layers Abliterated | 100% |
| Experts Abliterated | 100% |
| Scale | 0.95 |
| Winsorization | 0.995 |
LoRA Rank (r) | 16 |
| LoRA Alpha | 32 |