1.3 KiB
1.3 KiB
Figure Catalog
Figure 1 — Main comparison
- Filename:
figures/figure-01-main-comparison.pdf - Purpose: Compare WER across Full fine-tuning, Subject Adapter, and Frozen Encoder.
- Data source:
metrics/summary.csv - Plot type: Bar + scatter overlay of seed-level points.
- Error bars: 95% CI.
- Caption must include:
- metric direction,
- number of seeds,
- meaning of error bars,
- whether significance markers are corrected.
- Key observation: Subject Adapter closes most of the freezing gap.
- Interpretation checklist:
- Is the adapter improvement consistent across seeds?
- Is the gap practically meaningful, not just statistically significant?
- Does the figure support a design decision?
Figure 2 — Convergence dynamics
- Filename:
figures/figure-02-training-dynamics.pdf - Purpose: Compare optimization stability over epochs.
- Data source:
logs/train_curves.csv - Plot type: Mean line + uncertainty ribbon.
- Caption must include:
- smoothing rule if any,
- whether ribbon is std or CI,
- training/eval split.
- Key observation: Frozen Encoder shows larger oscillation after epoch 8.
- Interpretation checklist:
- Is instability transient or persistent?
- Does curve shape match final metric variance?
- Does this explain why one method is harder to tune?