📄 Plus¶
Tags: annotations_creators:expert-generated, language:en, language_creators:crowdsourced, license:cc-by-3.0, multilinguality:monolingual, region:us, size_categories:10K<n<100K, source_datasets:original, task_categories:text-classification, task_ids:intent-classification
Note
ID: cards.clinc_oos.plus | Type: TaskCard
{
"__description__": "Task-oriented dialog systems need to know when a query falls outside their range of supported intents, but current text classification corpora only define label sets that cover every example. We introduce a new dataset that includes queries that are out-of-scope (OOS), i.e., queries that do not fall into any of the system's supported intents. This poses a new challenge because models cannot assume that every query at… See the full description on the dataset page: https://huggingface.co/datasets/clinc_oos.",
"__tags__": {
"annotations_creators": "expert-generated",
"language": "en",
"language_creators": "crowdsourced",
"license": "cc-by-3.0",
"multilinguality": "monolingual",
"region": "us",
"size_categories": "10K<n<100K",
"source_datasets": "original",
"task_categories": "text-classification",
"task_ids": "intent-classification"
},
"__type__": "task_card",
"loader": {
"__type__": "load_hf",
"name": "plus",
"path": "clinc_oos"
},
"preprocess_steps": [
{
"__type__": "shuffle",
"page_size": 9223372036854775807
},
{
"__type__": "rename_fields",
"field_to_field": {
"intent": "label"
}
},
{
"__type__": "map_instance_values",
"mappers": {
"label": {
"0": "restaurant reviews",
"1": "nutrition info",
"10": "smart home",
"100": "rollover 401k",
"101": "pto request status",
"102": "how busy",
"103": "application status",
"104": "recipe",
"105": "calendar update",
"106": "play music",
"107": "yes",
"108": "direct deposit",
"109": "credit limit change",
"11": "user name",
"110": "gas",
"111": "pay bill",
"112": "ingredients list",
"113": "lost luggage",
"114": "goodbye",
"115": "what can i ask you",
"116": "book hotel",
"117": "are you a bot",
"118": "next song",
"119": "change speed",
"12": "report lost card",
"120": "plug type",
"121": "maybe",
"122": "w2",
"123": "oil change when",
"124": "thank you",
"125": "shopping list update",
"126": "pto balance",
"127": "order checks",
"128": "travel alert",
"129": "fun fact",
"13": "repeat",
"130": "sync device",
"131": "schedule maintenance",
"132": "apr",
"133": "transfer",
"134": "ingredient substitution",
"135": "calories",
"136": "current location",
"137": "international fees",
"138": "calculator",
"139": "definition",
"14": "whisper mode",
"140": "next holiday",
"141": "update playlist",
"142": "mpg",
"143": "min payment",
"144": "change user name",
"145": "restaurant suggestion",
"146": "travel notification",
"147": "cancel",
"148": "pto used",
"149": "travel suggestion",
"15": "what are your hobbies",
"150": "change volume",
"16": "order",
"17": "jump start",
"18": "schedule meeting",
"19": "meeting schedule",
"2": "account blocked",
"20": "freeze account",
"21": "what song",
"22": "meaning of life",
"23": "restaurant reservation",
"24": "traffic",
"25": "make call",
"26": "text",
"27": "bill balance",
"28": "improve credit score",
"29": "change language",
"3": "oil change how",
"30": "no",
"31": "measurement conversion",
"32": "timer",
"33": "flip coin",
"34": "do you have pets",
"35": "balance",
"36": "tell joke",
"37": "last maintenance",
"38": "exchange rate",
"39": "uber",
"4": "time",
"40": "car rental",
"41": "credit limit",
"42": "oos",
"43": "shopping list",
"44": "expiration date",
"45": "routing",
"46": "meal suggestion",
"47": "tire change",
"48": "todo list",
"49": "card declined",
"5": "weather",
"50": "rewards balance",
"51": "change accent",
"52": "vaccines",
"53": "reminder update",
"54": "food last",
"55": "change ai name",
"56": "bill due",
"57": "who do you work for",
"58": "share location",
"59": "international visa",
"6": "redeem rewards",
"60": "calendar",
"61": "translate",
"62": "carry on",
"63": "book flight",
"64": "insurance change",
"65": "todo list update",
"66": "timezone",
"67": "cancel reservation",
"68": "transactions",
"69": "credit score",
"7": "interest rate",
"70": "report fraud",
"71": "spending history",
"72": "directions",
"73": "spelling",
"74": "insurance",
"75": "what is your name",
"76": "reminder",
"77": "where are you from",
"78": "distance",
"79": "payday",
"8": "gas type",
"80": "flight status",
"81": "find phone",
"82": "greeting",
"83": "alarm",
"84": "order status",
"85": "confirm reservation",
"86": "cook time",
"87": "damaged card",
"88": "reset settings",
"89": "pin change",
"9": "accept reservations",
"90": "replacement card duration",
"91": "new card",
"92": "roll dice",
"93": "income",
"94": "taxes",
"95": "date",
"96": "who made you",
"97": "pto request",
"98": "tire pressure",
"99": "how old are you"
}
}
},
{
"__type__": "set",
"fields": {
"classes": [
"restaurant reviews",
"nutrition info",
"account blocked",
"oil change how",
"time",
"weather",
"redeem rewards",
"interest rate",
"gas type",
"accept reservations",
"smart home",
"user name",
"report lost card",
"repeat",
"whisper mode",
"what are your hobbies",
"order",
"jump start",
"schedule meeting",
"meeting schedule",
"freeze account",
"what song",
"meaning of life",
"restaurant reservation",
"traffic",
"make call",
"text",
"bill balance",
"improve credit score",
"change language",
"no",
"measurement conversion",
"timer",
"flip coin",
"do you have pets",
"balance",
"tell joke",
"last maintenance",
"exchange rate",
"uber",
"car rental",
"credit limit",
"oos",
"shopping list",
"expiration date",
"routing",
"meal suggestion",
"tire change",
"todo list",
"card declined",
"rewards balance",
"change accent",
"vaccines",
"reminder update",
"food last",
"change ai name",
"bill due",
"who do you work for",
"share location",
"international visa",
"calendar",
"translate",
"carry on",
"book flight",
"insurance change",
"todo list update",
"timezone",
"cancel reservation",
"transactions",
"credit score",
"report fraud",
"spending history",
"directions",
"spelling",
"insurance",
"what is your name",
"reminder",
"where are you from",
"distance",
"payday",
"flight status",
"find phone",
"greeting",
"alarm",
"order status",
"confirm reservation",
"cook time",
"damaged card",
"reset settings",
"pin change",
"replacement card duration",
"new card",
"roll dice",
"income",
"taxes",
"date",
"who made you",
"pto request",
"tire pressure",
"how old are you",
"rollover 401k",
"pto request status",
"how busy",
"application status",
"recipe",
"calendar update",
"play music",
"yes",
"direct deposit",
"credit limit change",
"gas",
"pay bill",
"ingredients list",
"lost luggage",
"goodbye",
"what can i ask you",
"book hotel",
"are you a bot",
"next song",
"change speed",
"plug type",
"maybe",
"w2",
"oil change when",
"thank you",
"shopping list update",
"pto balance",
"order checks",
"travel alert",
"fun fact",
"sync device",
"schedule maintenance",
"apr",
"transfer",
"ingredient substitution",
"calories",
"current location",
"international fees",
"calculator",
"definition",
"next holiday",
"update playlist",
"mpg",
"min payment",
"change user name",
"restaurant suggestion",
"travel notification",
"cancel",
"pto used",
"travel suggestion",
"change volume"
],
"text_type": "sentence",
"type_of_class": "intent"
}
}
],
"task": "tasks.classification.multi_class",
"templates": "templates.classification.multi_class.all"
}
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 LoadHF¶
Loads datasets from the Huggingface Hub.
It supports loading with or without streaming, and can filter datasets upon loading.
- Args:
path: The path or identifier of the dataset on the Huggingface Hub. name: An optional dataset name. data_dir: Optional directory to store downloaded data. split: Optional specification of which split to load. data_files: Optional specification of particular data files to load. streaming: Bool indicating if streaming should be used. filtering_lambda: A lambda function for filtering the data after loading. num_proc: Optional integer to specify the number of processes to use for parallel dataset loading.
- Example:
Loading glue’s mrpc dataset
load_hf = LoadHF(path='glue', name='mrpc')
Explanation about Shuffle¶
Shuffles the order of instances in each page of a stream.
- Args (of superclass):
page_size (int): The size of each page in the stream. Defaults to 1000.
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 Set¶
Adds specified fields to each instance in a given stream or all streams (default) If fields exist, updates them.
- Args:
- fields (Dict[str, object]): The fields to add to each instance.
Use ‘/’ to access inner fields
use_deepcopy (bool) : Deep copy the input value to avoid later modifications
- Examples:
# Add a ‘classes’ field with a value of a list “positive” and “negative” to all streams Set(fields={“classes”: [“positive”,”negatives”]})
# Add a ‘start’ field under the ‘span’ field with a value of 0 to all streams Set(fields={“span/start”: 0}
# Add a ‘classes’ field with a value of a list “positive” and “negative” to ‘train’ stream Set(fields={“classes”: [“positive”,”negatives”], apply_to_stream=[“train”]})
# Add a ‘classes’ field on a given list, prevent modification of original list # from changing the instance. Set(fields={“classes”: alist}), use_deepcopy=True) # if now alist is modified, still the instances remain intact.
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}}]
References: tasks.classification.multi_class, templates.classification.multi_class.all
Read more about catalog usage here.