📄 Both Games Gpt 4 Judge¶
Note
ID: cards.arena_hard.response_assessment.pairwise_comparative_rating.both_games_gpt_4_judge | Type: TaskCard
{
"__type__": "task_card",
"loader": {
"__type__": "load_from_hf_space",
"data_files": {
"judgment": "data/arena-hard-v0.1/model_judgment/gpt-4-1106-preview/*.jsonl",
"model_answer": "data/arena-hard-v0.1/model_answer/*.jsonl",
"questions": "data/arena-hard-v0.1/question.jsonl"
},
"revision": "03b91ca",
"space_name": "lmsys/arena-hard-browser"
},
"preprocess_steps": [
"operators.arena_hard_hf_space_processing_steps",
{
"__type__": "duplicate_split",
"split": "test",
"to_split": "game_2"
},
{
"__type__": "rename_fields",
"apply_to_streams": [
"test"
],
"field_to_field": {
"category": "group",
"model_1": "model_a",
"model_1_output": "answer_a",
"model_2": "model_b",
"model_2_output": "answer_b",
"model_input": "question",
"score_model_1_ordered_first": "answer_a_preference"
}
},
{
"__type__": "rename_fields",
"apply_to_streams": [
"game_2"
],
"field_to_field": {
"category": "group",
"model_1": "model_b",
"model_1_output": "answer_b",
"model_2": "model_a",
"model_2_output": "answer_a",
"model_input": "question",
"score_model_2_ordered_first": "answer_a_preference"
}
},
{
"__type__": "merge_streams",
"add_origin_stream_name": false,
"new_stream_name": "test",
"streams_to_merge": [
"test",
"game_2"
]
},
{
"__type__": "delete_splits",
"splits": [
"game_2"
]
},
{
"__type__": "map_instance_values",
"mappers": {
"answer_a_preference": {
"A=B": 0,
"A>>B": 3,
"A>B": 1,
"B>>A": -3,
"B>A": -1
}
}
}
],
"task": "tasks.response_assessment.pairwise_comparative_rating.single_turn",
"templates": [
"templates.response_assessment.pairwise_comparative_rating.arena_hard",
"templates.response_assessment.pairwise_comparative_rating.arena_hard_with_shuffling"
]
}
Explanation about TaskCard¶
TaskCard delineates the phases in transforming the source dataset into a model-input, and specifies the metrics for evaluation of model-output.
- Attributes:
loader: specifies the source address and the loading operator that can access that source and transform it into a unitxt multistream.
preprocess_steps: list of unitxt operators to process the data source into a model-input.
task: specifies the fields (of the already (pre)processed instance) making the inputs, the fields making the outputs, and the metrics to be used for evaluating the model output.
templates: format strings to be applied on the input fields (specified by the task) and the output fields. The template also carries the instructions and the list of postprocessing steps, to be applied to the model output.
Explanation about LoadFromHFSpace¶
Used to load data from Huggingface spaces.
Loaders firstly tries to download all files specified in the ‘data_files’ parameter from the given space and then reads them as a Huggingface dataset.
- Args:
space_name (str): Name of the Huggingface space to be accessed to. data_files (str | Sequence[str] | Mapping[str, str | Sequence[str]]): Relative
paths to files within a given repository. If given as a mapping, paths should be values, while keys should represent the type of respective files (training, testing etc.).
path (str, optional): Absolute path to a directory where data should be downloaded to. revision (str, optional): ID of a Git branch or commit to be used. By default, it is
set to None, thus data is downloaded from the main branch of the accessed repository.
- use_token (bool, optional): Whether token used for authentication when accessing
the Huggingface space - if necessary - should be read from the Huggingface config folder.
- token_env (str, optional): Key of an env variable which value will be used for
authentication when accessing the Huggingface space - if necessary.
- Example:
Loading from Huggingface Space
loader = LoadFromHFSpace( space_name="lmsys/mt-bench", data_files={ "train": [ "data/mt_bench/model_answer/gpt-3.5-turbo.jsonl", "data/mt_bench/model_answer/gpt-4.jsonl", ], "test": "data/mt_bench/model_answer/tulu-30b.jsonl", }, )
Explanation about DuplicateSplit¶
Operator which duplicate a split.
- Attributes:
split (str): The split to duplicate from the stream. to_split (str): The duplicate split’s name.
Explanation about DeleteSplits¶
Operator which delete splits in stream.
- Attributes:
splits (List[str]): The splits to delete from the stream.
Explanation about MapInstanceValues¶
A class used to map instance values into other values.
This class is a type of InstanceOperator, it maps values of instances in a stream using predefined mappers.
- Attributes:
- mappers (Dict[str, Dict[str, str]]): The mappers to use for mapping instance values.
Keys are the names of the fields to be mapped, and values are dictionaries that define the mapping from old values to new values.
- strict (bool): If True, the mapping is applied strictly. That means if a value
does not exist in the mapper, it will raise a KeyError. If False, values that are not present in the mapper are kept as they are.
- process_every_value (bool): If True, all fields to be mapped should be lists, and the mapping
is to be applied to their individual elements. If False, mapping is only applied to a field containing a single value.
- Examples:
MapInstanceValues(mappers={“a”: {“1”: “hi”, “2”: “bye”}}) replaces ‘1’ with ‘hi’ and ‘2’ with ‘bye’ in field ‘a’ in all instances of all streams: instance {“a”:”1”, “b”: 2} becomes {“a”:”hi”, “b”: 2}.
MapInstanceValues(mappers={“a”: {“1”: “hi”, “2”: “bye”}}, process_every_value=True) Assuming field ‘a’ is a list of values, potentially including “1”-s and “2”-s, this replaces each such “1” with “hi” and “2” – with “bye” in all instances of all streams: instance {“a”: [“1”, “2”], “b”: 2} becomes {“a”: [“hi”, “bye”], “b”: 2}.
MapInstanceValues(mappers={“a”: {“1”: “hi”, “2”: “bye”}}, strict=True) To ensure that all values of field ‘a’ are mapped in every instance, use strict=True. Input instance {“a”:”3”, “b”: 2} will raise an exception per the above call, because “3” is not a key in the mapper of “a”.
MapInstanceValues(mappers={“a”: {str([1,2,3,4]): ‘All’, str([]): ‘None’}}, strict=True) replaces a list [1,2,3,4] with the string ‘All’ and an empty list by string ‘None’. Note that mapped values are defined by their string representation, so mapped values must be converted to strings.
Explanation about RenameFields¶
Renames fields.
Move value from one field to another, potentially, if field name contains a /, from one branch into another. Remove the from field, potentially part of it in case of / in from_field.
- Examples:
RenameFields(field_to_field={“b”: “c”}) will change inputs [{“a”: 1, “b”: 2}, {“a”: 2, “b”: 3}] to [{“a”: 1, “c”: 2}, {“a”: 2, “c”: 3}]
RenameFields(field_to_field={“b”: “c/d”}) will change inputs [{“a”: 1, “b”: 2}, {“a”: 2, “b”: 3}] to [{“a”: 1, “c”: {“d”: 2}}, {“a”: 2, “c”: {“d”: 3}}]
RenameFields(field_to_field={“b”: “b/d”}) will change inputs [{“a”: 1, “b”: 2}, {“a”: 2, “b”: 3}] to [{“a”: 1, “b”: {“d”: 2}}, {“a”: 2, “b”: {“d”: 3}}]
RenameFields(field_to_field={“b/c/e”: “b/d”}) will change inputs [{“a”: 1, “b”: {“c”: {“e”: 2, “f”: 20}}}] to [{“a”: 1, “b”: {“c”: {“f”: 20}, “d”: 2}}]
Explanation about MergeStreams¶
Merges multiple streams into a single stream.
- Args:
new_stream_name (str): The name of the new stream resulting from the merge. add_origin_stream_name (bool): Whether to add the origin stream name to each instance. origin_stream_name_field_name (str): The field name for the origin stream name.
References: operators.arena_hard_hf_space_processing_steps, tasks.response_assessment.pairwise_comparative_rating.single_turn, templates.response_assessment.pairwise_comparative_rating.arena_hard, templates.response_assessment.pairwise_comparative_rating.arena_hard_with_shuffling
Read more about catalog usage here.