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thestarfarer
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Model Details
Model Provider
thestarfarer
Model Tree
mistralai/Ministral-3-14B-Base-2512
Input Modalities
Output Modalities
Supported Functionality
Multi-turn dialogue packed to 512-token samples — 13,667 samples,
6.16M tokens total. Turns are delimited by
# <code> headers — short per-character abbreviations, not names. Unattributed
narration is folded into the speaker's turn:
markdown
# mOkay.This is as far as I come.# sWe come to a stop in front of a tree positioned in the middle of three spotlights.It's not a particularly interesting tree or anything like that, so I'm a little confused as to why it's been so carefully illuminated.What is this?# mA tree, idiot.# sNo, like...what is this?
The pack was built in two phase-shifted passes — the second pass offsets every chunk boundary by 256 tokens, so the corpus appears twice with different windowing and exact-duplicate chunks removed. Experimental idea for cheap augmentation on small corpora; its actual effect is not isolated or evaluated in this repo.
Shared config: rsLoRA r512 / α512, dropout 0, targets q,k,v,o,gate,up,down,
batch 16 (no accumulation), 838 steps (one pass), constant LR after warmup,
BF16 base + FP32 AdamW, seed 42, eval on 256 held-out samples every 25 steps.
| run | path | init | LR | warmup | max_grad_norm | final eval |
|---|---|---|---|---|---|---|
v3-lil | / | continued from writer-sft-rp-v3 | 7.5e-6 | 30 | 10.0 | 1.530 |
base-lil | /base-lil/ | fresh adapter on base | 5e-6 | 35 | 10.0 | 1.582 |
base-lil-clip1 |
Init barely matters — according to metrics. base-lil matched v3-lil's
eval curve point-for-point for the first 250 steps and finished 0.05 behind at
33% lower LR — the 186M-token RP adapter it continues from bought approximately
nothing on this corpus by loss. Loss can't tell the whole story here: when the
two models miss, they might miss differently.
Gradient clipping at 1.0 changed nothing. base-lil-clip1 clipped on 100% of
steps (raw grad norms mean 14.9, max 36) and still landed within 0.001 of the
unclipped control. AdamW divides the first moment by the root second moment, so a
rescale applied to every gradient approximately cancels out of the update — clipping only
matters when it fires intermittently.
/gguf/ — F16 and Q8_0 for each run, merged into the base.
| file | size |
|---|---|
Ministral-3-14B-v3-lil-{F16,Q8_0}.gguf | 27.0 / 14.4 GB |
Ministral-3-14B-base-lil-{F16,Q8_0}.gguf | 27.0 / 14.4 GB |
Ministral-3-14B-base-clip1-{F16,Q8_0}.gguf | 27.0 / 14.4 GB |
/base-lil-clip1/ |
| fresh adapter on base |
| 5e-6 |
| 35 |
| 1.0 |
| 1.583 |