change displayed metrics

src/display/utils.py

@@ -8,10 +8,8 @@ from src.about import Tasks
 def fields(raw_class):
     return [v for k, v in raw_class.__dict__.items() if k[:2] != "__" and k[-2:] != "__"]
 
+from dataclasses import dataclass, make_dataclass
 
-# These classes are for user facing column names,
-# to avoid having to change them all around the code
-# when a modif is needed
 @dataclass
 class ColumnContent:
     name: str
@@ -20,28 +18,29 @@ class ColumnContent:
     hidden: bool = False
     never_hidden: bool = False
 
-## Leaderboard columns
-auto_eval_column_dict = []
-# Init
-# auto_eval_column_dict.append(["model_type_symbol", ColumnContent, ColumnContent("T", "str", True, never_hidden=True)])
-auto_eval_column_dict.append(["model_name", ColumnContent, ColumnContent("model_name", "markdown", True, never_hidden=True)])
-#Scores
-# auto_eval_column_dict.append(["average", ColumnContent, ColumnContent("Average ⬆️", "number", True)])
-auto_eval_column_dict.append(["accuracy", ColumnContent, ColumnContent("accuracy", "number", True)])
-for task in Tasks:
-    auto_eval_column_dict.append([task.name, ColumnContent, ColumnContent(task.value.col_name, "number", True)])
-# Model information
-auto_eval_column_dict.append(["model_type", ColumnContent, ColumnContent("Type", "str", False)])
-auto_eval_column_dict.append(["architecture", ColumnContent, ColumnContent("Architecture", "str", False)])
-auto_eval_column_dict.append(["weight_type", ColumnContent, ColumnContent("Weight type", "str", False, True)])
-auto_eval_column_dict.append(["precision", ColumnContent, ColumnContent("Precision", "str", False)])
-auto_eval_column_dict.append(["license", ColumnContent, ColumnContent("Hub License", "str", False)])
-auto_eval_column_dict.append(["params", ColumnContent, ColumnContent("#Params (B)", "number", False)])
-auto_eval_column_dict.append(["likes", ColumnContent, ColumnContent("Hub ❤️", "number", False)])
-auto_eval_column_dict.append(["still_on_hub", ColumnContent, ColumnContent("Available on the hub", "bool", False)])
-auto_eval_column_dict.append(["revision", ColumnContent, ColumnContent("Model sha", "str", False, False)])
-
-# We use make dataclass to dynamically fill the scores from Tasks
+# Dynamic fields based on new data schema
+metrics = ['precision', 'recall', 'f1_score', 'accuracy', 'yes_percent']
+auto_eval_column_dict = [
+    ["model_name", ColumnContent, ColumnContent("Model Name", "markdown", True, never_hidden=True)]
+]
+
+# Append metrics as dynamic columns
+for metric in metrics:
+    auto_eval_column_dict.append([metric, ColumnContent, ColumnContent(metric.capitalize() + " ⬆️", "number", True)])
+
+# Model information remains the same as needed
+auto_eval_column_dict += [
+    ["model_type", ColumnContent, ColumnContent("Type", "str", False)],
+    ["architecture", ColumnContent, ColumnContent("Architecture", "str", False)],
+    ["precision", ColumnContent, ColumnContent("Precision", "str", False)],  # Overlap with new metric name; might need renaming in context
+    ["license", ColumnContent, ColumnContent("Hub License", "str", False)],
+    ["params", ColumnContent, ColumnContent("#Params (B)", "number", False)],
+    ["likes", ColumnContent, ColumnContent("Hub ❤️", "number", False)],
+    ["still_on_hub", ColumnContent, ColumnContent("Available on the hub", "bool", False)],
+    ["revision", ColumnContent, ColumnContent("Model sha", "str", False, False)]
+]
+
+# Make the dataclass for AutoEvalColumn
 AutoEvalColumn = make_dataclass("AutoEvalColumn", auto_eval_column_dict, frozen=True)
 
 ## For the queue columns in the submission tab