- reports/degradation-analysis.md: interpretation of the one-parameter-at-a-time
ablations (ctx/short/small/data vs v1), grounded in val loss + sample text.
Key findings: held-out loss tracks quality for generalizing models; different
degradations give qualitatively different failure text; data-starvation
overfits (train ppl 1.1 / val ppl 322) with samples that hide the damage.
- reports/compare.md: side-by-side samples across all configs
- reports/loss-{small,short,ctx,data}.csv: variant training curves
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| 1 | iter | train_loss | val_loss | lr |
|---|---|---|---|---|
| 2 | 500 | 2.8303 | 2.8186 | 0.000564 |
| 3 | 1000 | 2.3438 | 2.3397 | 0.000377 |
| 4 | 1500 | 2.1359 | 2.1259 | 0.000156 |