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turnercore/lfm2.5-1.2b-automaticity-v9-lora

sourceHugging Faceotherupdated 3mo agoView on Hugging Face

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LFM2.5 1.2B + Automaticity V9 LoRA

Rank-16 response-only LoRA trained for one epoch on the private Automaticity V9 friendly direct-tool corpus. This is the strongest current V9 validation candidate, not a production-promoted autonomous router.

The model routes one current thought to at most one available tool, or makes no tool call. Training used LFM2.5's native marked Python-call-list format and loss only on the assistant turn.

Training

—Base: LiquidAI/LFM2.5-1.2B-Instruct
—Base/tokenizer revision: 868df74dd56ff8a0c2ac5dbf281690c2dbebe4c9
—Rows: 4,900; dataset SHA-256: 3fb79e5fe3cf762b3258c5674a806903e310aebb35d8ed153a525b0377b3bd8f
—Context: 2,048 tokens; no truncation; maximum rendered row 1,978 tokens
—Precision: ROCm BF16 LoRA, not QLoRA
—LoRA: rank 16, alpha 16, dropout 0; q/k/v/out/in_proj and w1/w2/w3
—Epochs: 1; linear learning-rate schedule; 3% warmup
—Peak learning rate: 2e-4; weight decay: 0.001
—Effective batch: 16 (4 x 4 gradient accumulation)
—Seed: 3407
—Loss: native assistant response only
—Trainer runtime: 4,037 seconds
—Adapter SHA-256: e81bdda7e1a684ae3a3f8d952303446d974c9ededf0cf383b8c76791112340ea

Frozen validation result

Evaluation used 1,050 private validation rows with normal five-tool retrieval, no gold injection, 100% action-gold retrieval recall, and no decoding constraint. The validation dataset SHA-256 is 85094c96ca7fa2f96cbb0f7f85bd08510d56b9d4639646156d8806680bca9715.

Metric	Result
End-to-end exact	95.33%
Routing	98.00%
Action exact	84.94%
No-tool precision	99.86%
No-tool recall	99.73%
Argument schema validity	99.90%
Listed-tool rate	99.90%
Valid-call rate	100%
Latency average	1.242 s
Latency p50	0.518 s
Latency p95	4.520 s
No-tool latency average / p95	0.471 s / 0.661 s
Action latency average / p95	3.065 s / 8.413 s

The untuned base on the identical ROCm validation condition scored 32.29% end-to-end exact, 45.52% routing, 29.17% action exact, and 33.60% no-tool recall.

Limitations

This adapter is not yet promoted for autonomous execution. The frozen validation set still contains 20 wrong-tool rows, 28 wrong-argument rows, and one unlisted call. Action p95 latency is 8.413 seconds, 6.3% slower than the untuned action p95 even though aggregate latency improved substantially. Use strict listed-name and schema validation or constrained decoding and reject invalid calls at runtime. Constraints cannot repair semantically wrong listed tools or schema-valid wrong arguments.

The private dataset and row-level evaluation repository is turnercore/automaticity-v9.