hma / common /plot /plot_pretrain_ablation.py
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import seaborn as sns
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
font = {
"family": "normal",
"size": 22,
}
matplotlib.rc("font", **font)
sns.set(rc={"font.family": "Times New Roman"})
sns.set(style="whitegrid")
sns.set(font_scale=3, style="whitegrid")
# Sample data for plotting
categories = ["Scratch", "Passive Pre-Train", "Pre-Train", "Pre-Train (Large)"]
values = [1.0, 1.0, 1.0, 1.0]
# Define custom colors for the bars
colors = ["#4c72b0", "#55a868", "#c44e52", "#8172b2"] # Adjust as needed
plt.figure(figsize=(14, 12))
ax = sns.barplot(
x=categories, y=values, alpha=0.9, palette=colors, edgecolor="black"
)
for container in ax.containers:
ax.bar_label(container, label_type="edge", fontsize="x-large", fmt="%.2f")
# Adding title and labels
plt.xlabel("Setting", fontsize=40)
plt.ylabel("Validation Perplexity", fontsize=40)
plt.xticks(fontsize=30)
plt.yticks(fontsize=30)
plt.legend(fontsize="small", title_fontsize="small", loc="lower left")
# Remove the borders
sns.despine(left=True, bottom=True)
# Display the plot
plt.tight_layout()
plt.savefig(f"output/model_ablation.png", dpi=300) # Save the figure in high resolution
plt.show()