add cb metrics

lm_eval/tasks/super_glue/cb/t5_utils.py

+import sklearn.metrics
+
+def mean_3class_f1(predictions, references):  # This is a passthrough function
+
+    string_label = ['entailment', 'contradiction', 'neutral']
+    predictions = string_label.index(predictions[0])
+    references = string_label.index(references[0])
+
+    return (predictions, references)
+
+def agg_mean_3class_f1(items):
+
+    predictions, references = zip(*items)
+
+    """Computes the unweighted average of the F1 per class."""
+    metric_str = "fbeta_score"
+    metric_post_process_fn = lambda x: x
+    metric_fn_kwargs = {
+        "beta": 1,
+        "labels": range(3),
+        "average": "macro",
+    }
+
+    def _fn(predictions, references):
+        metric_fn = getattr(sklearn.metrics, metric_str)
+        metric_val = metric_fn(references, predictions, **metric_fn_kwargs)
+        if metric_post_process_fn is not None:
+            metric_val = metric_post_process_fn(metric_val)
+        return metric_val
+
+    return _fn(predictions, references)