Unverified Commit 3d1b8f43 authored by Lintang Sutawika's avatar Lintang Sutawika Committed by GitHub
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Merge branch 'main' into group-agg-rework

parents e200c24e d855d0ba
dataset_name: logical_deduction_seven_objects
description: 'A logical deduction task which requires deducing the order of a sequence
of objects.
'
doc_to_choice: ["(A)","(B)","(C)","(D)","(E)","(F)","(G)"]
fewshot_config:
sampler: first_n
samples:
- input: 'The following paragraphs each describe a set of three objects arranged
in a fixed order. The statements are logically consistent within each paragraph.
In a golf tournament, there were three golfers: Amy, Eli, and Eve. Eve finished
above Amy. Eli finished below Amy.
Options:
(A) Amy finished last
(B) Eli finished last
(C) Eve finished last'
target: (B)
- input: 'The following paragraphs each describe a set of three objects arranged
in a fixed order. The statements are logically consistent within each paragraph.
On a shelf, there are three books: a white book, a green book, and an orange
book. The green book is to the right of the white book. The orange book is the
rightmost.
Options:
(A) The white book is the leftmost
(B) The green book is the leftmost
(C) The orange book is the leftmost'
target: (A)
- input: 'The following paragraphs each describe a set of three objects arranged
in a fixed order. The statements are logically consistent within each paragraph.
On a shelf, there are three books: a red book, a gray book, and a white book.
The white book is to the left of the gray book. The red book is the second from
the left.
Options:
(A) The red book is the leftmost
(B) The gray book is the leftmost
(C) The white book is the leftmost'
target: (C)
include: _fewshot_template_yaml
task: leaderboard_bbh_logical_deduction_seven_objects
dataset_name: logical_deduction_three_objects
description: 'A logical deduction task which requires deducing the order of a sequence
of objects.
'
doc_to_choice: ["(A)","(B)","(C)"]
fewshot_config:
sampler: first_n
samples:
- input: 'The following paragraphs each describe a set of three objects arranged
in a fixed order. The statements are logically consistent within each paragraph.
In a golf tournament, there were three golfers: Amy, Eli, and Eve. Eve finished
above Amy. Eli finished below Amy.
Options:
(A) Amy finished last
(B) Eli finished last
(C) Eve finished last'
target: (B)
- input: 'The following paragraphs each describe a set of three objects arranged
in a fixed order. The statements are logically consistent within each paragraph.
On a shelf, there are three books: a white book, a green book, and an orange
book. The green book is to the right of the white book. The orange book is the
rightmost.
Options:
(A) The white book is the leftmost
(B) The green book is the leftmost
(C) The orange book is the leftmost'
target: (A)
- input: 'The following paragraphs each describe a set of three objects arranged
in a fixed order. The statements are logically consistent within each paragraph.
On a shelf, there are three books: a red book, a gray book, and a white book.
The white book is to the left of the gray book. The red book is the second from
the left.
Options:
(A) The red book is the leftmost
(B) The gray book is the leftmost
(C) The white book is the leftmost'
target: (C)
include: _fewshot_template_yaml
task: leaderboard_bbh_logical_deduction_three_objects
dataset_name: movie_recommendation
description: 'Recommend movies similar to the given list of movies.
'
doc_to_choice: ["(A)","(B)","(C)","(D)","(E)","(F)"]
fewshot_config:
sampler: first_n
samples:
- input: 'Find a movie similar to Star Wars Episode IV - A New Hope, Indiana Jones
and the Last Crusade, Star Wars Episode V - The Empire Strikes Back, The Big
Lebowski:
Options:
(A) Tetsuo
(B) the Ironman
(C) The Princess Bride
(D) The Barkley Marathons The Race That Eats Its Young
(E) Bug'
target: (C)
- input: 'Find a movie similar to Twister, The Silence of the Lambs, Independence
Day, Braveheart:
Options:
(A) They Shoot Horses
(B) Don''t They
(C) Forrest Gump
(D) The Salton Sea
(E) Extreme Days'
target: (C)
- input: 'Find a movie similar to Minority Report, Total Recall, Inside Out, Forrest
Gump:
Options:
(A) Phenomena
(B) Lilting
(C) Catwoman
(D) Edge of Tomorrow'
target: (D)
include: _fewshot_template_yaml
task: leaderboard_bbh_movie_recommendation
dataset_name: navigate
description: 'Given a series of navigation instructions, determine whether one would
end up back at the starting point.
'
doc_to_choice: ["Yes","No"]
fewshot_config:
sampler: first_n
samples:
- input: 'If you follow these instructions, do you return to the starting point?
Turn left. Turn around. Turn left. Take 7 steps. Take 2 steps. Take 4 steps.
Take 8 steps.
Options:
- Yes
- No'
target: 'No'
- input: 'If you follow these instructions, do you return to the starting point?
Turn around. Take 1 step. Take 6 steps. Turn around. Take 6 steps. Take 9 steps.
Take 1 step.
Options:
- Yes
- No'
target: 'No'
- input: 'If you follow these instructions, do you return to the starting point?
Always face forward. Take 2 steps right. Take 9 steps left. Take 7 steps right.
Options:
- Yes
- No'
target: 'Yes'
include: _fewshot_template_yaml
task: leaderboard_bbh_navigate
dataset_name: object_counting
description: 'Questions that involve enumerating objects and asking the model to count
them.
'
doc_to_choice: ["0","1","2","3","4","5","6","7","8","9","10", "11", "12", "13", "14", "15", "16", "17", "18"]
fewshot_config:
sampler: first_n
samples:
- input: I have a blackberry, a clarinet, a nectarine, a plum, a strawberry, a banana,
a flute, an orange, and a violin. How many fruits do I have?
target: '6'
- input: I have an orange, a raspberry, two peaches, a blackberry, an apple, a grape,
a nectarine, and three plums. How many fruits do I have?
target: '11'
- input: I have a lettuce head, a head of broccoli, an onion, a stalk of celery,
two carrots, a garlic, and a yam. How many vegetables do I have?
target: '8'
include: _fewshot_template_yaml
task: leaderboard_bbh_object_counting
dataset_name: penguins_in_a_table
description: 'Answer questions about a table of penguins and their attributes.
'
doc_to_choice: ["(A)","(B)","(C)","(D)","(E)"]
fewshot_config:
sampler: first_n
samples:
- input: 'Here is a table where the first line is a header and each subsequent line
is a penguin: name, age, height (cm), weight (kg) Louis, 7, 50, 11 Bernard,
5, 80, 13 Vincent, 9, 60, 11 Gwen, 8, 70, 15 For example: the age of Louis
is 7, the weight of Gwen is 15 kg, the height of Bernard is 80 cm. We now add
a penguin to the table:
James, 12, 90, 12
How many penguins are less than 8 years old?
Options:
(A) 1
(B) 2
(C) 3
(D) 4
(E) 5'
target: (B)
- input: 'Here is a table where the first line is a header and each subsequent line
is a penguin: name, age, height (cm), weight (kg) Louis, 7, 50, 11 Bernard,
5, 80, 13 Vincent, 9, 60, 11 Gwen, 8, 70, 15 For example: the age of Louis
is 7, the weight of Gwen is 15 kg, the height of Bernard is 80 cm. Which is
the youngest penguin?
Options:
(A) Louis
(B) Bernard
(C) Vincent
(D) Gwen
(E) James'
target: (B)
- input: 'Here is a table where the first line is a header and each subsequent line
is a penguin: name, age, height (cm), weight (kg) Louis, 7, 50, 11 Bernard,
5, 80, 13 Vincent, 9, 60, 11 Gwen, 8, 70, 15 For example: the age of Louis
is 7, the weight of Gwen is 15 kg, the height of Bernard is 80 cm. What is
the name of the second penguin sorted by alphabetic order?
Options:
(A) Louis
(B) Bernard
(C) Vincent
(D) Gwen
(E) James'
target: (D)
include: _fewshot_template_yaml
task: leaderboard_bbh_penguins_in_a_table
dataset_name: reasoning_about_colored_objects
description: 'Answer extremely simple questions about the colors of objects on a surface.
'
doc_to_choice: ["(A)","(B)","(C)","(D)","(E)","(F)","(G)","(H)","(I)","(J)","(K)","(L)","(M)","(N)","(O)","(P)","(Q)","(R)"]
fewshot_config:
sampler: first_n
samples:
- input: 'On the nightstand, there is a red pencil, a purple mug, a burgundy keychain,
a fuchsia teddy bear, a black plate, and a blue stress ball. What color is the
stress ball?
Options:
(A) red
(B) orange
(C) yellow
(D) green
(E) blue
(F) brown
(G) magenta
(H) fuchsia
(I) mauve
(J) teal
(K) turquoise
(L) burgundy
(M) silver
(N) gold
(O) black
(P) grey
(Q) purple
(R) pink'
target: (E)
- input: 'On the table, you see a bunch of objects arranged in a row: a purple paperclip,
a pink stress ball, a brown keychain, a green scrunchiephone charger, a mauve
fidget spinner, and a burgundy pen. What is the color of the object directly
to the right of the stress ball?
Options:
(A) red
(B) orange
(C) yellow
(D) green
(E) blue
(F) brown
(G) magenta
(H) fuchsia
(I) mauve
(J) teal
(K) turquoise
(L) burgundy
(M) silver
(N) gold
(O) black
(P) grey
(Q) purple
(R) pink'
target: (F)
- input: 'On the nightstand, you see the following items arranged in a row: a teal
plate, a burgundy keychain, a yellow scrunchiephone charger, an orange mug,
a pink notebook, and a grey cup. How many non-orange items do you see to the
left of the teal item?
Options:
(A) zero
(B) one
(C) two
(D) three
(E) four
(F) five
(G) six'
target: (A)
include: _fewshot_template_yaml
task: leaderboard_bbh_reasoning_about_colored_objects
dataset_name: ruin_names
description: 'Select the humorous edit that ''ruins'' the input movie or musical artist
name.
'
doc_to_choice: ["(A)","(B)","(C)","(D)","(E)","(F)"]
fewshot_config:
sampler: first_n
samples:
- input: 'Which of the following is a humorous edit of this artist or movie name:
''whitesnake''?
Options:
(A) whitesnape
(B) whitesnapke
(C) whitesnuake
(D) mwhitesnake'
target: (A)
- input: 'Which of the following is a humorous edit of this artist or movie name:
''one of our dinosaurs is missing''?
Options:
(A) ofne of our dinosaurs is missing
(B) one af our dinosaurs is missing
(C) one of our dinosaurs is pissing
(D) one of our dinosaur is missing'
target: (C)
- input: 'Which of the following is a humorous edit of this artist or movie name:
''counting crows''?
Options:
(A) countingy crows
(B) counting cows
(C) courting crows
(D) coutnting crows'
target: (B)
include: _fewshot_template_yaml
task: leaderboard_bbh_ruin_names
dataset_name: salient_translation_error_detection
description: 'Detect the type of error in an English translation of a German source
sentence.
'
doc_to_choice: ["(A)","(B)","(C)","(D)","(E)","(F)"]
fewshot_config:
sampler: first_n
samples:
- input: "The following translations from German to English contain a particular
error. That error will be one of the following types: Named Entities: An entity
(names, places, locations, etc.) is changed to a different entity. Numerical
Values: Numerical values (ordinals or cardinals), dates, and/or units are changed.
Modifiers or Adjectives: The modifiers and adjectives pertaining to a noun are
changed. Negation or Antonyms: Introduce or remove a negation or change comparatives
to their antonyms. Facts: Trivial factual errors not pertaining to the above
classes are introduced in the translations. Dropped Content: A significant clause
in the translation is removed. Please identify that error. Source: In der Liste
der Baudenkmale in Lenzen (Elbe) sind alle Baudenkmale der brandenburgischen
Stadt Lenzen (Elbe) und ihrer Ortsteile aufgelistet.
Translation: In the list of architectural monuments in Lenzen all architectural
monuments of the Brandenburg city of Lenzen and its districts are listed.
The translation contains an error pertaining to
Options:
(A) Modifiers or Adjectives
(B) Numerical Values
(C) Negation or Antonyms
(D) Named Entities
(E) Dropped Content
(F) Facts"
target: (D)
- input: "The following translations from German to English contain a particular
error. That error will be one of the following types: Named Entities: An entity
(names, places, locations, etc.) is changed to a different entity. Numerical
Values: Numerical values (ordinals or cardinals), dates, and/or units are changed.
Modifiers or Adjectives: The modifiers and adjectives pertaining to a noun are
changed. Negation or Antonyms: Introduce or remove a negation or change comparatives
to their antonyms. Facts: Trivial factual errors not pertaining to the above
classes are introduced in the translations. Dropped Content: A significant clause
in the translation is removed. Please identify that error. Source: Auf dieser
Seite sind die Baudenkm\xE4ler der oberbayerischen Gro\xDFen Kreisstadt Landsberg
am Lech zusammengestellt.
Translation: On this page are compiled the architectural monuments of the town of
Landsberg am Lech.
The translation contains an error pertaining to
Options:
(A) Modifiers or Adjectives
(B) Numerical Values
(C) Negation or Antonyms
(D) Named Entities
(E) Dropped Content
(F) Facts"
target: (E)
- input: "The following translations from German to English contain a particular
error. That error will be one of the following types: Named Entities: An entity
(names, places, locations, etc.) is changed to a different entity. Numerical
Values: Numerical values (ordinals or cardinals), dates, and/or units are changed.
Modifiers or Adjectives: The modifiers and adjectives pertaining to a noun are
changed. Negation or Antonyms: Introduce or remove a negation or change comparatives
to their antonyms. Facts: Trivial factual errors not pertaining to the above
classes are introduced in the translations. Dropped Content: A significant clause
in the translation is removed. Please identify that error. Source: \u0141eba ist
eine Kleinstadt und ein Badeort im Powiat L\u0119borski der polnischen Woiwodschaft
Pommern.
Translation: Eba is not a small town and seaside resort in the Powiat L\xE9borski
county of the Pomeranian Voivodeship of Poland.\nThe translation contains an error
pertaining to
Options:
(A) Modifiers or Adjectives
(B) Numerical Values
(C) Negation or Antonyms
(D) Named Entities
(E) Dropped Content
(F) Facts"
target: (C)
include: _fewshot_template_yaml
task: leaderboard_bbh_salient_translation_error_detection
dataset_name: snarks
description: 'Determine which of two sentences is sarcastic.
According to Cambridge University Dictionary, sarcasm is "the use of remarks that
clearly mean the opposite of what they say, made in order to hurt someone''s feelings
or to criticize something in a humorous way." Sarcastic sentences often contain
satirical or ironic utterances, hyperboles, ambivalent or witty remarks.
'
doc_to_choice: ["(A)","(B)"]
fewshot_config:
sampler: first_n
samples:
- input: 'Which statement is sarcastic?
Options:
(A) Yes, because having interests and actively researching them is a huge waste
(B) Yes, because having interests and actively researching them is a huge deal'
target: (A)
- input: 'Which statement is sarcastic?
Options:
(A) No one is going to disagree with you on this. Avoiding ad hominem attacks
really help your case
(B) No one is going to disagree with you on this. Ad hominem attacks really
help your case'
target: (B)
- input: 'Which statement is sarcastic?
Options:
(A) Consistency in the league''s punishments? What do you think this is supposed
to be, politics?
(B) Consistency in the league''s punishments? What do you think this is supposed
to be, moral?'
target: (A)
include: _fewshot_template_yaml
task: leaderboard_bbh_snarks
dataset_name: sports_understanding
description: 'Determine whether an artificially constructed sentence relating to sports
is plausible or not.
'
doc_to_choice: ["yes","no"]
fewshot_config:
sampler: first_n
samples:
- input: Is the following sentence plausible? "Bam Adebayo scored a reverse layup
in the Western Conference Finals."
target: 'yes'
- input: Is the following sentence plausible? "Santi Cazorla scored a touchdown."
target: 'no'
- input: Is the following sentence plausible? "DeMar DeRozan was called for the
goal tend."
target: 'yes'
include: _fewshot_template_yaml
task: leaderboard_bbh_sports_understanding
dataset_name: temporal_sequences
description: 'Task description: Answer questions about which times certain events
could have occurred.
'
doc_to_choice: ["(A)","(B)","(C)","(D)"]
fewshot_config:
sampler: first_n
samples:
- input: 'Today, Emily went to the museum. Between what times could they have gone?
We know that:
Emily woke up at 1pm.
Elizabeth saw Emily reading at the library from 2pm to 4pm.
Jessica saw Emily watching a movie at the theater from 4pm to 5pm.
Leslie saw Emily waiting at the airport from 5pm to 6pm.
William saw Emily buying clothes at the mall from 6pm to 7pm.
The museum was closed after 7pm.
Between what times could Emily have gone to the museum?
Options:
(A) 1pm to 2pm
(B) 6pm to 7pm
(C) 5pm to 6pm
(D) 2pm to 4pm'
target: (A)
- input: 'Today, Elizabeth went to the amusement park. Between what times could
they have gone?
We know that:
Elizabeth woke up at 7am.
David saw Elizabeth fixing their computer at the electronic store from 1pm to
2pm.
Sarah saw Elizabeth playing tennis at the tennis court from 2pm to 3pm.
Susan saw Elizabeth walking towards the Statue of Liberty from 3pm to 6pm.
Andrew saw Elizabeth taking photos near the Eiffel Tower from 6pm to 9pm.
Emily saw Elizabeth getting a coffee at the cafe from 9pm to 10pm.
The amusement park was closed after 10pm.
Between what times could Elizabeth have gone to the amusement park?
Options:
(A) 7am to 1pm
(B) 9pm to 10pm
(C) 1pm to 2pm
(D) 3pm to 6pm'
target: (A)
- input: 'Today, Tiffany went to the beach. Between what times could they have gone?
We know that:
Tiffany woke up at 5am.
Betty saw Tiffany getting a coffee at the cafe from 5am to 6am.
Jessica saw Tiffany working at the office from 6am to 9am.
John saw Tiffany stretching at a yoga studio from 9am to 12pm.
Sean saw Tiffany sitting on a rooftop from 12pm to 2pm.
Sarah saw Tiffany playing tennis at the tennis court from 2pm to 3pm.
The beach was closed after 4pm.
Between what times could Tiffany have gone to the beach?
Options:
(A) 9am to 12pm
(B) 12pm to 2pm
(C) 5am to 6am
(D) 3pm to 4pm'
target: (D)
include: _fewshot_template_yaml
task: leaderboard_bbh_temporal_sequences
dataset_name: tracking_shuffled_objects_five_objects
description: 'A task requiring determining the final positions of a set of objects
given their initial positions and a description of a sequence of swaps.
'
doc_to_choice: ["(A)","(B)","(C)","(D)","(E)"]
fewshot_config:
sampler: first_n
samples:
- input: 'Alice, Bob, and Claire are playing a game. At the start of the game, they
are each holding a ball: Alice has a yellow ball, Bob has a blue ball, and Claire
has a pink ball.
As the game progresses, pairs of players trade balls. First, Claire and Alice
swap balls. Then, Alice and Bob swap balls. Finally, Claire and Bob swap balls.
At the end of the game, Bob has the
Options:
(A) yellow ball
(B) blue ball
(C) pink ball'
target: (A)
- input: 'Alice, Bob, and Claire are playing a game. At the start of the game, they
are each holding a ball: Alice has a white ball, Bob has a purple ball, and
Claire has a pink ball.
As the game progresses, pairs of players trade balls. First, Bob and Alice swap
balls. Then, Bob and Claire swap balls. Finally, Bob and Alice swap balls. At
the end of the game, Alice has the
Options:
(A) white ball
(B) purple ball
(C) pink ball'
target: (C)
- input: 'Alice, Bob, and Claire are dancers at a square dance. At the start of
a song, they each have a partner: Alice is dancing with Lola, Bob is dancing
with Rodrigo, and Claire is dancing with Patrick.
Throughout the song, the dancers often trade partners. First, Alice and Bob
switch partners. Then, Claire and Bob switch partners. Finally, Bob and Alice
switch partners. At the end of the dance, Alice is dancing with
Options:
(A) Lola
(B) Rodrigo
(C) Patrick'
target: (C)
include: _fewshot_template_yaml
task: leaderboard_bbh_tracking_shuffled_objects_five_objects
dataset_name: tracking_shuffled_objects_seven_objects
description: 'A task requiring determining the final positions of a set of objects
given their initial positions and a description of a sequence of swaps.
'
doc_to_choice: ["(A)","(B)","(C)","(D)","(E)","(F)","(G)"]
fewshot_config:
sampler: first_n
samples:
- input: 'Alice, Bob, and Claire are playing a game. At the start of the game, they
are each holding a ball: Alice has a yellow ball, Bob has a blue ball, and Claire
has a pink ball.
As the game progresses, pairs of players trade balls. First, Claire and Alice
swap balls. Then, Alice and Bob swap balls. Finally, Claire and Bob swap balls.
At the end of the game, Bob has the
Options:
(A) yellow ball
(B) blue ball
(C) pink ball'
target: (A)
- input: 'Alice, Bob, and Claire are playing a game. At the start of the game, they
are each holding a ball: Alice has a white ball, Bob has a purple ball, and
Claire has a pink ball.
As the game progresses, pairs of players trade balls. First, Bob and Alice swap
balls. Then, Bob and Claire swap balls. Finally, Bob and Alice swap balls. At
the end of the game, Alice has the
Options:
(A) white ball
(B) purple ball
(C) pink ball'
target: (C)
- input: 'Alice, Bob, and Claire are dancers at a square dance. At the start of
a song, they each have a partner: Alice is dancing with Lola, Bob is dancing
with Rodrigo, and Claire is dancing with Patrick.
Throughout the song, the dancers often trade partners. First, Alice and Bob
switch partners. Then, Claire and Bob switch partners. Finally, Bob and Alice
switch partners. At the end of the dance, Alice is dancing with
Options:
(A) Lola
(B) Rodrigo
(C) Patrick'
target: (C)
include: _fewshot_template_yaml
task: leaderboard_bbh_tracking_shuffled_objects_seven_objects
dataset_name: tracking_shuffled_objects_three_objects
description: 'A task requiring determining the final positions of a set of objects
given their initial positions and a description of a sequence of swaps.
'
doc_to_choice: ["(A)","(B)","(C)"]
fewshot_config:
sampler: first_n
samples:
- input: 'Alice, Bob, and Claire are playing a game. At the start of the game, they
are each holding a ball: Alice has a yellow ball, Bob has a blue ball, and Claire
has a pink ball.
As the game progresses, pairs of players trade balls. First, Claire and Alice
swap balls. Then, Alice and Bob swap balls. Finally, Claire and Bob swap balls.
At the end of the game, Bob has the
Options:
(A) yellow ball
(B) blue ball
(C) pink ball'
target: (A)
- input: 'Alice, Bob, and Claire are playing a game. At the start of the game, they
are each holding a ball: Alice has a white ball, Bob has a purple ball, and
Claire has a pink ball.
As the game progresses, pairs of players trade balls. First, Bob and Alice swap
balls. Then, Bob and Claire swap balls. Finally, Bob and Alice swap balls. At
the end of the game, Alice has the
Options:
(A) white ball
(B) purple ball
(C) pink ball'
target: (C)
- input: 'Alice, Bob, and Claire are dancers at a square dance. At the start of
a song, they each have a partner: Alice is dancing with Lola, Bob is dancing
with Rodrigo, and Claire is dancing with Patrick.
Throughout the song, the dancers often trade partners. First, Alice and Bob
switch partners. Then, Claire and Bob switch partners. Finally, Bob and Alice
switch partners. At the end of the dance, Alice is dancing with
Options:
(A) Lola
(B) Rodrigo
(C) Patrick'
target: (C)
include: _fewshot_template_yaml
task: leaderboard_bbh_tracking_shuffled_objects_three_objects
dataset_name: web_of_lies
description: 'Evaluate a random boolean function expressed as a word problem.
'
doc_to_choice: ["Yes","No"]
fewshot_config:
sampler: first_n
samples:
- input: 'Question: Fidel tells the truth. Jerry says Fidel tells the truth. Vina
says Jerry tells the truth. Millicent says Vina lies. Raymond says Millicent
lies. Does Raymond tell the truth?'
target: 'Yes'
- input: 'Question: Kristian lies. Millie says Kristian lies. Maybelle says Millie
tells the truth. Fidel says Maybelle lies. Leda says Fidel lies. Does Leda tell
the truth?'
target: 'Yes'
- input: 'Question: Kristian tells the truth. Michaela says Kristian lies. Raymond
says Michaela tells the truth. Osvaldo says Raymond tells the truth. Jamey says
Osvaldo tells the truth. Does Jamey tell the truth?'
target: 'No'
include: _fewshot_template_yaml
task: leaderboard_bbh_web_of_lies
dataset_path: Idavidrein/gpqa
group: leaderboard_gpqa
output_type: multiple_choice
process_docs: !function utils.process_docs
training_split: train
# Because huggingface dataset only has train split
validation_split: train
test_split: null
doc_to_text: "What is the correct answer to this question:{{Question}}\nChoices:\n(A) {{choice1}}\n(B) {{choice2}}\n(C) {{choice3}}\n(D) {{choice4}}\nAnswer: "
doc_to_target: answer
doc_to_choice: ["(A)", "(B)", "(C)", "(D)"]
num_fewshot: 0
metric_list:
- metric: acc_norm
aggregation: mean
higher_is_better: true
metadata:
version: 1.0
fewshot_config:
sampler: first_n
# Generated by _generate_configs.py
dataset_name: gpqa_diamond
include: _template_yaml
task: leaderboard_gpqa_diamond
# Generated by _generate_configs.py
dataset_name: gpqa_extended
include: _template_yaml
task: leaderboard_gpqa_extended
# Generated by _generate_configs.py
dataset_name: gpqa_main
include: _template_yaml
task: leaderboard_gpqa_main
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