{% extends "base.html" %} {% block content %} {# ── Page header ── #}
Results
Review model evaluation metrics and decide which model to export
{% if not runs %} {# ── No results yet ── #} {% else %} {# ── Run selector ── #}
Select run: {% for r in runs %} {{ r.name }} {% endfor %} {% if runs | length > 1 %} | Compare: {% for r in runs %} {% if r.name != selected_run %} vs {{ r.name }} {% endif %} {% endfor %} {% endif %}
{# ── Instructions banner ── #} {% if eval_report %}
{# ── Leaderboard ── #}
Evaluation Metrics — {{ selected_run }} {% if eval_report.plugin_name %}{{ eval_report.plugin_name }}{% endif %}
{% for k, v in eval_report.metrics.items() %} {% endfor %}
MetricValue
{{ k }} {{ "%.4f" | format(v) }} {% if k in ("accuracy", "f1", "auc") %} higher = better {% elif k in ("rmse", "mae") %} lower = better {% endif %}
{# ── Feature importance ── #} {% if eval_report.feature_importance %}
Feature Importance (SHAP)
{% for feat, score in eval_report.feature_importance.items() %} {% endfor %}
{{ feat }}
{{ "%.3f" | format(score) }}
Higher bar = stronger influence on predictions. Low-importance columns can be removed to simplify the model.
{% endif %}
{# ── Run comparison ── #} {% if compare_report %}
Comparing {{ selected_run }} vs {{ compare_run }}
{% for k in all_metrics %} {% set va = eval_report.metrics.get(k) %} {% set vb = compare_report.metrics.get(k) %} {% endfor %}
Metric{{ selected_run }}{{ compare_run }}Delta
{{ k }} {% if va is not none %}{{ "%.4f" | format(va) }}{% else %}—{% endif %} {% if vb is not none %}{{ "%.4f" | format(vb) }}{% else %}—{% endif %} {% if va is not none and vb is not none %} {% set delta = vb - va %} {{ "%+.4f" | format(delta) }} {% else %}—{% endif %}
{% endif %} {# ── Bar chart ── #}
{% if eval_report.metrics %} {% endif %} {# ── Next steps ── #}
What to do next

Happy with results?

1. Go to Pipeline and click Approve on the review_results gate.

2. Run aimodelground run to export the model and generate your deployment guide.

Want to improve?

- Tune hyperparameters: aimodelground tune --trials 50

- Re-run from training with new config: aimodelground run --from train_rf

- Compare another run: click a run button above and add ?compare=run_001 to the URL.

{% else %}
No evaluation report found for {{ selected_run }}. The run may not have completed training yet.
{% endif %} {% endif %} {% endblock %}