Small changes
Browse files
app.py
CHANGED
@@ -48,7 +48,7 @@ def mean_of_max_per_field(df):
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def boxplot_per_task(dataframe=None, baselines=None):
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print(dataframe.columns)
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tasks = ["TE", "SA", "HS", "AT", "WIC", "FAQ", "LS", "SU", "NER", "REL"]
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@@ -76,7 +76,6 @@ def boxplot_per_task(dataframe=None, baselines=None):
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y=y_data,
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name=task,
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marker=dict(color=colors[i]),
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# Modifica: Impostiamo il colore della linea della scatola su un colore diverso dal riempimento
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line=dict(color="black", width=2),
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fillcolor=colors[i],
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opacity=0.7,
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@@ -105,8 +104,8 @@ def boxplot_per_task(dataframe=None, baselines=None):
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fig.update_layout(
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title="Distribution of Model Accuracy by Task",
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xaxis_title="Task",
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yaxis_title="
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template="plotly_white",
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boxmode="group",
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dragmode=False,
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@@ -119,7 +118,7 @@ def boxplot_per_task(dataframe=None, baselines=None):
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"indicate best-performing supervised models evaluated on EVALITA."
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),
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xref="paper", yref="paper",
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x=0.5, y=-0.
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showarrow=False,
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font=dict(size=12, color="gray")
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)
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@@ -130,7 +129,6 @@ def boxplot_per_task(dataframe=None, baselines=None):
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return fig
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# 🔹 Esempio d’uso
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BASELINES = {
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"TE":71.00, "SA": 66.38, "HS": 80.88, "AT": 82.40, "WIC": 85.00,
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"LS": 38.82, "SU": 38.91, "NER":88.00, "REL": 62.99
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@@ -187,16 +185,16 @@ def boxplot_prompts_per_task(dataframe, tasks=None):
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for x, y, text in zip(best_x, best_y, best_text):
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fig.add_annotation(
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x=x,
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y=y +
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text=text,
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showarrow=False,
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font=dict(size=12, color="black")
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)
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fig.update_layout(
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title="
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xaxis_title="Task",
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yaxis_title="
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barmode='group',
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template="plotly_white",
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font=dict(family="Arial", size=13),
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def boxplot_per_task(dataframe=None, baselines=None):
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+
#print(dataframe.columns)
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tasks = ["TE", "SA", "HS", "AT", "WIC", "FAQ", "LS", "SU", "NER", "REL"]
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y=y_data,
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name=task,
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marker=dict(color=colors[i]),
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line=dict(color="black", width=2),
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fillcolor=colors[i],
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opacity=0.7,
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fig.update_layout(
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title="Distribution of Model Accuracy by Task",
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#xaxis_title="Task",
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yaxis_title="Avg. Combined Performance ⬆️",
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template="plotly_white",
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boxmode="group",
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dragmode=False,
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"indicate best-performing supervised models evaluated on EVALITA."
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),
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xref="paper", yref="paper",
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x=0.5, y=-0.30,
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showarrow=False,
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font=dict(size=12, color="gray")
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)
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return fig
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BASELINES = {
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"TE":71.00, "SA": 66.38, "HS": 80.88, "AT": 82.40, "WIC": 85.00,
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"LS": 38.82, "SU": 38.91, "NER":88.00, "REL": 62.99
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for x, y, text in zip(best_x, best_y, best_text):
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fig.add_annotation(
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x=x,
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y=y + 3, # leggermente sopra la barra
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text=text,
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showarrow=False,
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font=dict(size=12, color="black")
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)
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fig.update_layout(
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title="Average Prompt Accuracy vs Best Prompt Accuracy per Task",
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xaxis_title="Task",
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yaxis_title="Avg. Combined Performance ⬆️",
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barmode='group',
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template="plotly_white",
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font=dict(family="Arial", size=13),
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