Scores by Task

Overview

The scores_by_task() function renders a bar plot for comparing eval scores.

from inspect_viz import Data
from inspect_viz.view.beta import scores_by_task

evals = Data.from_file("evals.parquet")
scores_by_task(evals)

Data Preparation

Above we read the data for the plot from a parquet file. This file was in turn created by:

Reading logs into a data frame with evals_df().
Using the prepare() function to add model_info() and log_viewer() columns to the data frame.

from inspect_ai.analysis import evals_df, log_viewer, model_info, prepare

df = evals_df("logs")
df = prepare(df, [
    model_info(),
    log_viewer("eval", {"logs": "https://samples.meridianlabs.ai/"})
])
df.to_parquet("evals.parquet")

You can additionally use the task_info() operation to map lower-level task names to task display names (e.g. “gpqa_diamond” -> “GPQA Diamond”).

Note that both the log viewer links and model names are optional (the plot will render without links and use raw model strings if the data isn’t prepared with log_viewer() and model_info()).

Function Reference

Bar plot for comparing eval scores.

Summarize eval scores using a bar plot. By default, scores (y) are plotted by “task_display_name” (fx) and “model_display_name” (x). By default, confidence intervals are also plotted (disable this with y_ci=False).

Source

def scores_by_task(
    data: Data,
    model_name: str = "model_display_name",
    task_name: str = "task_display_name",
    score_value: str = "score_headline_value",
    score_stderr: str = "score_headline_stderr",
    score_label: str | None | NotGiven = NOT_GIVEN,
    ci: bool | float = 0.95,
    title: str | Title | None = None,
    marks: Marks | None = None,
    width: float | Param | None = None,
    height: float | Param | None = None,
    legend: Legend | NotGiven | None = NOT_GIVEN,
    **attributes: Unpack[PlotAttributes],
) -> Component

data Data: Evals data table. This is typically created using a data frame read with the inspect evals_df() function.
model_name str: Name of field for the model name (defaults to “model_display_name”)
task_name str: Name of field for the task name (defaults to “task_display_name”)
score_value str: Name of field for the score value (defaults to “score_headline_value”).
score_stderr str: Name of field for stderr (defaults to “score_headline_metric”).
score_label str | None | NotGiven: Score axis label (pass None for no label).
ci bool | float: Confidence interval (e.g. 0.80, 0.90, 0.95, etc.). Defaults to 0.95.
title str | Title | None: Title for plot (str or mark created with the title() function).
marks Marks | None: Additional marks to include in the plot.
width float | Param | None: The outer width of the plot in pixels, including margins. Defaults to 700.
height float | Param | None: The outer height of the plot in pixels, including margins. The default is width / 1.618 (the golden ratio)
legend Legend | NotGiven | None: Options for the legend. Pass None to disable the legend.
**attributes Unpack[PlotAttributes]: Additional PlotAttributes. By default, the margin_bottom are is set to 10 pixels and x_ticks is set to [].

Implementation

The Scores by Task example demonstrates how this view was implemented using lower level plotting components.