📄 Plus¶
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, category:dataset
cards.clinc_oos.plus
TaskCard(
loader=LoadHF(
path="clinc/clinc_oos",
name="plus",
),
preprocess_steps=[
Shuffle(
page_size=9223372036854775807,
),
Rename(
field_to_field={
"intent": "label",
},
),
MapInstanceValues(
mappers={
"label": {
"0": "restaurant reviews",
"1": "nutrition info",
"2": "account blocked",
"3": "oil change how",
"4": "time",
"5": "weather",
"6": "redeem rewards",
"7": "interest rate",
"8": "gas type",
"9": "accept reservations",
"10": "smart home",
"11": "user name",
"12": "report lost card",
"13": "repeat",
"14": "whisper mode",
"15": "what are your hobbies",
"16": "order",
"17": "jump start",
"18": "schedule meeting",
"19": "meeting schedule",
"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",
"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",
"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",
"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",
"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",
"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",
"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",
"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",
"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",
"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",
"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",
"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",
"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",
"150": "change volume",
},
},
),
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",
)
[source]from unitxt.loaders import LoadHF
from unitxt.operators import MapInstanceValues, Rename, Set, Shuffle
Explanation about TaskCard¶
TaskCard delineates the phases in transforming the source dataset into model input, and specifies the metrics for evaluation of model output.
- Args:
- 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 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 Set¶
Sets specified fields in each instance, in a given stream or all streams (default), with specified values. If fields exist, updates them, if do not exist – adds 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:
# Set a value of a list consisting of “positive” and “negative” do field “classes” to each and every instance of all streams
Set(fields={"classes": ["positive","negatives"]})# In each and every instance of all streams, field “span” is to become a dictionary containing a field “start”, in which the value 0 is to be set
Set(fields={"span/start": 0}# In all instances of stream “train” only, Set field “classes” to have the value of a list consisting of “positive” and “negative”
Set(fields={"classes": ["positive","negatives"], apply_to_stream=["train"]})# Set field “classes” to have the value of a given list, preventing 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 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 Rename¶
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:
Rename(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}]
Rename(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}}]
Rename(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}}]
Rename(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 LoadHF¶
Loads datasets from the HuggingFace Hub.
It supports loading with or without streaming, and it 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. When you provide a list of data_files to Hugging Face’s load_dataset function without explicitly specifying the split argument, these files are automatically placed into the train split.
- revision:
Optional. The revision of the dataset. Often the commit id. Use in case you want to set the dataset version.
- streaming (bool):
indicating if streaming should be used.
- filtering_lambda (str, optional):
A lambda function for filtering the data after loading.
- num_proc (int, optional):
Specifies 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 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.
- Args:
- mappers (Dict[str, Dict[str, Any]]):
The mappers to use for mapping instance values. Keys are the names of the fields to undergo mapping, and values are dictionaries that define the mapping from old values to new values. Note that mapped values are defined by their string representation, so mapped values are converted to strings before being looked up in the mappers.
- 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}. Note that the value of"b"remained intact, since field-name"b"does not participate in the mappers, and that1was casted to"1"before looked up in the mapper of"a".
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, usestrict=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".
References: templates.classification.multi_class.all, tasks.classification.multi_class
Read more about catalog usage here.