ducanhdinh / Macro-Nano-Instruct-Finetuning

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Total runs: 1.5K
24-hour runs: -55
7-day runs: -522
30-day runs: -1.3K
Model's Last Updated: August 30 2026

Introduction of Macro-Nano-Instruct-Finetuning

Model Details of Macro-Nano-Instruct-Finetuning

Macro-Nano-Instruct-Finetuning

Day la LoRA adapter finetune tu ATH-MaaS/Marco-Nano-Instruct , mot mo hinh Mixture-of-Experts.

Cau hinh LoRA
  • Layer duoc finetune: [9, 18) trong tong so 28 layer (tuong ung khoang 1L/3 -> 2L/3).
  • Module duoc gan LoRA: attention , router , experts trong khoang layer tren.
  • r = 16, alpha = 32, dropout = 0.05
Loss

Loss MoE tieu chuan:

L_total = L_LM + lb_loss_coef * L_LB

  • L_LM : cross-entropy chuan tren token tiep theo.
  • L_LB : load balancing loss chuan cua MoE (Switch/Mixtral style), tinh tren cac router nam trong khoang layer duoc finetune.
  • lb_loss_coef = None
  • num_experts = 232, top_k = 8
Du lieu

Cau don ngu duoc gom tu 3 bo du lieu alignment: flores.json , bible.json , ntrex.json (moi field ngon ngu trong 1 record duoc coi la 1 sample), shuffle va sort theo do dai token truoc khi gom batch.

Diagnostics

Xem diagnostics/loss_log.jsonl (log theo tung step) va diagnostics/loss_curve.png (bieu do L_LM / L_LB / L_Total theo step).

Runs of ducanhdinh Macro-Nano-Instruct-Finetuning on huggingface.co

1.5K
Total runs
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24-hour runs
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3-day runs
-522
7-day runs
-1.3K
30-day runs

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https://huggingface.co/ducanhdinh/Macro-Nano-Instruct-Finetuning

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Macro-Nano-Instruct-Finetuning install

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Updated:November 24 2025