diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md
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+++ b/lm_eval/tasks/README.md
@@ -26,6 +26,7 @@
 | [ceval](ceval/README.md) | Tasks that evaluate language understanding and reasoning in an educational context. | Chinese |
 | [cmmlu](cmmlu/README.md) | Multi-subject multiple choice question tasks for comprehensive academic assessment. | Chinese |
 | code_x_glue | Tasks that involve understanding and generating code across multiple programming languages. | Go, Java, JS, PHP, Python, Ruby |
+| [commonsense_qa](commmonsense_qa/README.md) | CommonsenseQA, a multiple-choice QA dataset for measuring commonsense knowledge. | English |
 | [copal_id](copal_id/README.md) | Indonesian causal commonsense reasoning dataset that captures local nuances. | Indonesian |
 | [coqa](coqa/README.md) | Conversational question answering tasks to test dialog understanding. | English |
 | [crows_pairs](crows_pairs/README.md) | Tasks designed to test model biases in various sociodemographic groups. | English, French |
diff --git a/lm_eval/tasks/commonsense_qa/README.md b/lm_eval/tasks/commonsense_qa/README.md
new file mode 100644
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+++ b/lm_eval/tasks/commonsense_qa/README.md
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+# Task-name
+
+### Paper
+
+Title: `COMMONSENSEQA: A Question Answering Challenge Targeting
+Commonsense Knowledge`
+
+Abstract: https://arxiv.org/pdf/1811.00937.pdf
+
+CommonsenseQA is a multiple-choice question answering dataset that requires different types of commonsense knowledge to predict the correct answers.
+It contains 12,102 questions with one correct answer and four distractor answers.
+
+Homepage: https://www.tau-nlp.org/commonsenseqa
+
+
+### Citation
+
+```
+@inproceedings{talmor-etal-2019-commonsenseqa,
+    title = "{C}ommonsense{QA}: A Question Answering Challenge Targeting Commonsense Knowledge",
+    author = "Talmor, Alon  and
+      Herzig, Jonathan  and
+      Lourie, Nicholas  and
+      Berant, Jonathan",
+    booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
+    month = jun,
+    year = "2019",
+    address = "Minneapolis, Minnesota",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/N19-1421",
+    doi = "10.18653/v1/N19-1421",
+    pages = "4149--4158",
+    archivePrefix = "arXiv",
+    eprint        = "1811.00937",
+    primaryClass  = "cs",
+}
+```
+
+### Groups and Tasks
+
+#### Groups
+
+* Not part of a group yet.
+
+#### Tasks
+
+* `commonsense_qa`: Represents the "random" split from the paper. Uses an MMLU-style prompt, as (presumably) used by Llama evaluations.
+
+### Checklist
+
+For adding novel benchmarks/datasets to the library:
+* [x] Is the task an existing benchmark in the literature?
+  * [x] Have you referenced the original paper that introduced the task?
+  * [x] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?
+
+
+If other tasks on this dataset are already supported:
+* [ ] Is the "Main" variant of this task clearly denoted?
+* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates?
+* [ ] Have you noted which, if any, published evaluation setups are matched by this variant?
diff --git a/lm_eval/tasks/commonsense_qa/default.yaml b/lm_eval/tasks/commonsense_qa/default.yaml
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+++ b/lm_eval/tasks/commonsense_qa/default.yaml
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+task: commonsense_qa
+dataset_path: tau/commonsense_qa
+training_split: train
+validation_split: validation
+output_type: multiple_choice
+doc_to_text: "Question: {{ question.strip() }}\nA. {{choices['text'][0]}}\nB. {{choices['text'][1]}}\nC. {{choices['text'][2]}}\nD. {{choices['text'][3]}}\nE. {{choices['text'][4]}}\nAnswer:"
+doc_to_target: answerKey
+doc_to_choice: ['A', 'B', 'C', 'D', 'E']
+metric_list:
+  - metric: acc
+    aggregation: mean
+    higher_is_better: true