File size: 3,400 Bytes
26f2cbf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 | """Plot variance analysis results for SmolLM (Math), Qwen3 (Math), Maze."""
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np
import os
SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
OUTPUT_DIR = os.path.join(SCRIPT_DIR, "outputs")
os.makedirs(OUTPUT_DIR, exist_ok=True)
# ── Data ──────────────────────────────────────────────────────────────────────
rollout_nums = [4, 8, 16, 32, 64, 128]
smollm_math = {
"blTrue": [3.461569e-01, 3.488942e-01, 2.763410e-01, 2.600237e-01, 2.039304e-01, 1.596079e-01],
"blFalse": [5.613685e-01, 4.680250e-01, 3.457040e-01, 2.965937e-01, 2.275286e-01, 1.723276e-01],
}
qwen3_math = {
"blTrue": [1.544762e-01, 1.679264e-01, 2.075920e-01, 1.788574e-01, 1.592376e-01, 1.314381e-01],
"blFalse": [2.140592e-01, 2.190761e-01, 2.448343e-01, 2.002312e-01, 1.702958e-01, 1.390878e-01],
}
maze = {
"blTrue": [9.343412e-02, 7.531368e-02, 5.179188e-02, 4.027390e-02, 2.930888e-02, 2.354821e-02],
"blFalse": [1.171640e-01, 8.123477e-02, 5.614680e-02, 4.236686e-02, 3.015591e-02, 2.521931e-02],
}
datasets = [
("SmolLM-360M (GSM8k)", smollm_math),
("Qwen3-1.7B (Polaris-53K)", qwen3_math),
("Qwen2-3M (Maze)", maze),
]
# ── Style ─────────────────────────────────────────────────────────────────────
plt.rcParams.update({
"font.size": 15,
"axes.titlesize": 18,
"axes.labelsize": 16,
"legend.fontsize": 14,
"xtick.labelsize": 14,
"ytick.labelsize": 14,
"figure.dpi": 150,
"savefig.dpi": 300,
"font.family": "sans-serif",
})
RED = "#D32F2F"
AMBER = "#F9A825"
# ── Plot ──────────────────────────────────────────────────────────────────────
fig, axes = plt.subplots(1, 3, figsize=(21, 6))
for ax, (title, data) in zip(axes, datasets):
xs = np.array(rollout_nums)
bl_true = np.array([v if v is not None else np.nan for v in data["blTrue"]])
bl_false = np.array([v if v is not None else np.nan for v in data["blFalse"]])
ax.plot(xs, bl_true, color=RED, marker="*", markersize=18, linewidth=4,
label="MaxRL", zorder=5)
ax.plot(xs, bl_false, color=AMBER, marker="o", markersize=11, linewidth=4,
label="MaxRL (w/o baseline)", zorder=4)
ax.set_xscale("log", base=2)
ax.set_xticks(rollout_nums)
ax.set_xticklabels([str(n) for n in rollout_nums])
ax.set_xlabel("Number of Rollouts", fontsize=16)
ax.set_ylabel("Gradient Variance", fontsize=16)
ax.set_title(title, fontsize=18, fontweight="bold", pad=12)
ax.legend(loc="upper right", framealpha=0.9, edgecolor="gray")
ax.grid(True, alpha=0.3, linestyle="--")
ax.spines["top"].set_visible(False)
ax.spines["right"].set_visible(False)
plt.tight_layout(w_pad=3)
out_path = os.path.join(OUTPUT_DIR, "variance_comparison_all.png")
plt.savefig(out_path, bbox_inches="tight")
plt.savefig(out_path.replace(".png", ".pdf"), bbox_inches="tight")
print(f"Saved to {out_path}")
|