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agg_functions.py

@@ -0,0 +1,54 @@
+from typing import List
+
+import numpy as np
+
+
+try:
+    import tinyBenchmarks as tb
+except ModuleNotFoundError:
+    raise ModuleNotFoundError(
+        "`tinyBenchmarks` is required for tinyBenchmarks task metric calculation, install via \
+`pip install git+https://github.com/felipemaiapolo/tinyBenchmarks`"
+    )
+
+
+def agg_pirt(items: List[float], benchmark: str) -> float:
+    items = np.array(items)
+    predictions = tb.evaluate(items, benchmark)
+    return predictions[benchmark]["pirt"]
+
+
+def agg_gpirt_arc(items: List[float], benchmark: str = "arc") -> float:
+    items = np.array(items)
+    predictions = tb.evaluate(items, benchmark)
+    return predictions[benchmark]["gpirt"]
+
+
+def agg_gpirt_gsm8k(items: List[float], benchmark: str = "gsm8k") -> float:
+    items = np.array(items)
+    predictions = tb.evaluate(items, benchmark)
+    return predictions[benchmark]["gpirt"]
+
+
+def agg_gpirt_hellaswag(items: List[float], benchmark: str = "hellaswag") -> float:
+    items = np.array(items)
+    predictions = tb.evaluate(items, benchmark)
+    return predictions[benchmark]["gpirt"]
+
+
+def agg_gpirt_mmlu(items: List[float], benchmark: str = "mmlu") -> float:
+    items = np.array(items)
+    predictions = tb.evaluate(items, benchmark)
+    return predictions[benchmark]["gpirt"]
+
+
+def agg_gpirt_truthfulqa(items: List[float], benchmark: str = "truthfulqa") -> float:
+    items = np.array(items)
+    predictions = tb.evaluate(items, benchmark)
+    return predictions[benchmark]["gpirt"]
+
+
+def agg_gpirt_winogrande(items: List[float], benchmark: str = "winogrande") -> float:
+    items = np.array(items)
+    predictions = tb.evaluate(items, benchmark)
+    return predictions[benchmark]["gpirt"]

arc_commonsense.yaml

@@ -1,4 +1,4 @@
-task: arc_commonsense
+task: arc_challenge
 dataset_path: CultriX/arc-challenge-train-100
 task: arc_challenge
 dataset_path: allenai/ai2_arc

tinyArc.yaml

@@ -0,0 +1,22 @@
+
+task: tinyArc
+dataset_path: tinyBenchmarks/tinyAI2_arc
+dataset_name: ARC-Challenge
+output_type: multiple_choice
+training_split: train
+validation_split: validation
+test_split: test
+num_fewshot: 25
+doc_to_text: "Question: {{question}}
+Answer:"
+doc_to_target: "{{choices.label.index(answerKey)}}"
+doc_to_choice: "{{choices.text}}"
+should_decontaminate: true
+doc_to_decontamination_query: "Question: {{question}}
+Answer:"
+metric_list:
+  - metric: acc_norm
+    aggregation: !function agg_functions.agg_gpirt_arc
+    higher_is_better: true
+metadata:
+  version: 0.0