reports/lora_r16_12k_run_report.md

LFM2.5 Hermes Tool-Trace LoRA Run Report

Outcome

Completed a local MLX LoRA fine-tune for LiquidAI/LFM2.5-8B-A1B-MLX-bf16 on Hermes-style tool traces. The final adapter reloads, the fused MLX checkpoint loads, and the fixed mini-suite shows a small tool-format improvement over the baseline GGUF server.

GGUF export is blocked in mlx-lm for this architecture:

ValueError: Model type lfm2_moe not supported for GGUF conversion.

Environment

• mlx: 0.31.2
• mlx-lm: 0.31.3
• datasets: 4.8.5
• transformers: 5.9.0
• huggingface_hub: 1.17.0
• Python: /opt/homebrew/bin/python3 via lfm25_hermes_ft/venv

Dataset

Source dataset: DJLougen/hermes-agent-traces-filtered, default/train.

Initial 16K artifact:

• Input rows: 3,679
• Accepted rows at 16K cap: 1,583
• Split: 1,431 train, 90 valid, 62 test
• Rejected as over 16K: 2,077
• Rejected as malformed/unbalanced: 19

The requested 16K training pass was attempted and failed with Metal OOM. A deterministic 12K view was created from the accepted 16K artifact:

• Train: 880 kept, 551 dropped from 16K artifact
• Valid: 47 kept, 43 dropped from 16K artifact
• Test: 36 kept, 26 dropped from 16K artifact

Training

Final training config:

• Model: LiquidAI/LFM2.5-8B-A1B-MLX-bf16
• Data: lfm25_hermes_ft/datasets/hermes_filtered_text_12k
• LoRA rank: 16
• LoRA layers: 16
• Batch size: 1
• Gradient accumulation: 1
• Max sequence length: 12,000
• Iterations: 880
• Learning rate: 1e-5
• Validation batches: 1
• Gradient checkpointing: enabled
• Seed: 42

Final training line:

Iter 880: Val loss 0.465, Train loss 0.278, Tokens/sec 974.875, Trained Tokens 7501092, Peak mem 50.948 GB

Evaluation

Fixed six-case Hermes mini-suite:

• Single weather tool call
• Web search tool call
• Calculator tool call
• Tool-response finalization
• No-tool natural response
• Malformed-tool robustness

Results:

Lane	Passed	Parseable tool calls
Baseline GGUF server	3 / 6	0
MLX LoRA adapter	4 / 6	1

The adapter produced a valid Hermes XML/JSON tool call for the web-search case:

<tool_call>
{"name": "web_search", "arguments": {"query": "Liquid AI LFM2.5 release notes"}}
</tool_call>

It did not yet reliably force tool calls for weather or calculator prompts.

Artifacts

• Final adapter: lfm25_hermes_ft/checkpoints/hermes_lora_r16_12k/adapters.safetensors
• Adapter checkpoints: lfm25_hermes_ft/checkpoints/hermes_lora_r16_12k/0000100_adapters.safetensors through 0000800_adapters.safetensors
• Fused MLX checkpoint: lfm25_hermes_ft/artifacts/hermes_lora_r16_12k_fused_mlx
• Eval JSON: lfm25_hermes_ft/evals/hermes_tool_eval.json
• Training log: lfm25_hermes_ft/logs/train_lora.log
• GGUF blocker log: lfm25_hermes_ft/logs/fuse_export_gguf.log
• OOM evidence:
  • lfm25_hermes_ft/logs/train_lora_oom_val4_with_server.log
  • lfm25_hermes_ft/logs/train_lora_oom_val1_no_server.log
  • lfm25_hermes_ft/logs/train_lora_oom_gradaccum1_no_server.log

Status

This run is useful as a retained MLX adapter/fused checkpoint, but it is not llama.cpp-ready because GGUF export for lfm2_moe is unsupported by the installed mlx-lm exporter.