Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

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+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
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+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
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+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- crowdsourced
+languages:
+- en
+licenses:
+- cc-by-3-0
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- intent-classification
+---
+
+# Dataset Card for [Dataset Name]
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** [Github](https://github.com/clinc/oos-eval/)
+- **Repository:** [Github](https://github.com/clinc/oos-eval/)
+- **Paper:** [Aclweb](https://www.aclweb.org/anthology/D19-1131)
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+[More Information Needed]
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+[More Information Needed]
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]

clinc_oos.py

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+"""An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction"""
+
+from __future__ import absolute_import, division, print_function
+
+import json
+import textwrap
+
+import datasets
+
+
+_CITATION = """\
+    @inproceedings{larson-etal-2019-evaluation,
+    title = "An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction",
+    author = "Larson, Stefan  and
+      Mahendran, Anish  and
+      Peper, Joseph J.  and
+      Clarke, Christopher  and
+      Lee, Andrew  and
+      Hill, Parker  and
+      Kummerfeld, Jonathan K.  and
+      Leach, Kevin  and
+      Laurenzano, Michael A.  and
+      Tang, Lingjia  and
+      Mars, Jason",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
+    year = "2019",
+    url = "https://www.aclweb.org/anthology/D19-1131"
+}
+"""
+
+_DESCRIPTION = """\
+    This dataset is for evaluating the performance of intent classification systems in the
+    presence of "out-of-scope" queries. By "out-of-scope", we mean queries that do not fall
+    into any of the system-supported intent classes. Most datasets include only data that is
+    "in-scope". Our dataset includes both in-scope and out-of-scope data. You might also know
+    the term "out-of-scope" by other terms, including "out-of-domain" or "out-of-distribution".
+"""
+
+_DESCRIPTIONS = {
+    "small": textwrap.dedent(
+        """\
+        Small, in which there are only 50 training queries per each in-scope intent
+        """
+    ),
+    "imbalanced": textwrap.dedent(
+        """\
+        Imbalanced, in which intents have either 25, 50, 75, or 100 training queries.
+        """
+    ),
+    "plus": textwrap.dedent(
+        """\
+        OOS+, in which there are 250 out-of-scope training examples, rather than 100.
+        """
+    ),
+}
+
+_URL = "https://github.com/clinc/oos-eval/"
+
+_DATA_URLS = {
+    "small": "https://raw.githubusercontent.com/clinc/oos-eval/master/data/data_small.json",
+    "imbalanced": "https://raw.githubusercontent.com/clinc/oos-eval/master/data/data_imbalanced.json",
+    "plus": "https://raw.githubusercontent.com/clinc/oos-eval/master/data/data_oos_plus.json",
+}
+
+
+class ClincConfig(datasets.BuilderConfig):
+
+    """BuilderConfig for CLINC150"""
+
+    def __init__(self, description, data_url, citation, url, **kwrags):
+        """
+        Args:
+            description: `string`, brief description of the dataset
+            data_url: `dictionary`, dict with url for each split of data.
+            citation: `string`, citation for the dataset.
+            url: `string`, url for information about the dataset.
+            **kwrags: keyword arguments frowarded to super
+        """
+        super(ClincConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwrags)
+        self.description = description
+        self.data_url = data_url
+        self.citation = citation
+        self.url = url
+
+
+class ClincOos(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        ClincConfig(
+            name=name, description=_DESCRIPTIONS[name], data_url=_DATA_URLS[name], citation=_CITATION, url=_URL
+        )
+        for name in ["small", "imbalanced", "plus"]
+    ]
+
+    def _info(self):
+        features = {}
+        features["text"] = datasets.Value("string")
+        labels_list = [
+            "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",
+        ]
+        features["intent"] = datasets.ClassLabel(names=labels_list)
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION + "\n" + self.config.description,
+            features=datasets.Features(features),
+            homepage=self.config.url,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        file_ = dl_manager.download_and_extract(self.config.data_url)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": file_, "split": "train"}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": file_, "split": "val"}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": file_, "split": "test"}),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        with open(filepath, encoding="utf-8") as f:
+            j = json.load(f)
+            for id_, row in enumerate(j[split] + j["oos_" + split]):
+                yield id_, {"text": row[0], "intent": row[1]}

dataset_infos.json

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+{"small": {"description": "    This dataset is for evaluating the performance of intent classification systems in the\n    presence of \"out-of-scope\" queries. By \"out-of-scope\", we mean queries that do not fall\n    into any of the system-supported intent classes. Most datasets include only data that is\n    \"in-scope\". Our dataset includes both in-scope and out-of-scope data. You might also know\n    the term \"out-of-scope\" by other terms, including \"out-of-domain\" or \"out-of-distribution\".\n\nSmall, in which there are only 50 training queries per each in-scope intent\n", "citation": "    @inproceedings{larson-etal-2019-evaluation,\n    title = \"An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction\",\n    author = \"Larson, Stefan  and\n      Mahendran, Anish  and\n      Peper, Joseph J.  and\n      Clarke, Christopher  and\n      Lee, Andrew  and\n      Hill, Parker  and\n      Kummerfeld, Jonathan K.  and\n      Leach, Kevin  and\n      Laurenzano, Michael A.  and\n      Tang, Lingjia  and\n      Mars, Jason\",\n    booktitle = \"Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)\",\n    year = \"2019\",\n    url = \"https://www.aclweb.org/anthology/D19-1131\"\n}\n", "homepage": "https://github.com/clinc/oos-eval/", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "intent": {"num_classes": 151, "names": ["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"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "clinc_oos", "config_name": "small", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 394128, "num_examples": 7600, "dataset_name": "clinc_oos"}, "validation": {"name": "validation", "num_bytes": 160302, "num_examples": 3100, "dataset_name": "clinc_oos"}, "test": {"name": "test", "num_bytes": 286970, "num_examples": 5500, "dataset_name": "clinc_oos"}}, "download_checksums": {"https://raw.githubusercontent.com/clinc/oos-eval/master/data/data_small.json": {"num_bytes": 1702451, "checksum": "050e17476e6b4fa88f8518edaf09921c8f5e3a86dc8b63615361102a20b2ac01"}}, "download_size": 1702451, "post_processing_size": null, "dataset_size": 841400, "size_in_bytes": 2543851}, "imbalanced": {"description": "    This dataset is for evaluating the performance of intent classification systems in the\n    presence of \"out-of-scope\" queries. By \"out-of-scope\", we mean queries that do not fall\n    into any of the system-supported intent classes. Most datasets include only data that is\n    \"in-scope\". Our dataset includes both in-scope and out-of-scope data. You might also know\n    the term \"out-of-scope\" by other terms, including \"out-of-domain\" or \"out-of-distribution\".\n\nImbalanced, in which intents have either 25, 50, 75, or 100 training queries.\n", "citation": "    @inproceedings{larson-etal-2019-evaluation,\n    title = \"An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction\",\n    author = \"Larson, Stefan  and\n      Mahendran, Anish  and\n      Peper, Joseph J.  and\n      Clarke, Christopher  and\n      Lee, Andrew  and\n      Hill, Parker  and\n      Kummerfeld, Jonathan K.  and\n      Leach, Kevin  and\n      Laurenzano, Michael A.  and\n      Tang, Lingjia  and\n      Mars, Jason\",\n    booktitle = \"Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)\",\n    year = \"2019\",\n    url = \"https://www.aclweb.org/anthology/D19-1131\"\n}\n", "homepage": "https://github.com/clinc/oos-eval/", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "intent": {"num_classes": 151, "names": ["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"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "clinc_oos", "config_name": "imbalanced", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 546909, "num_examples": 10625, "dataset_name": "clinc_oos"}, "validation": {"name": "validation", "num_bytes": 160302, "num_examples": 3100, "dataset_name": "clinc_oos"}, "test": {"name": "test", "num_bytes": 286970, "num_examples": 5500, "dataset_name": "clinc_oos"}}, "download_checksums": {"https://raw.githubusercontent.com/clinc/oos-eval/master/data/data_imbalanced.json": {"num_bytes": 2016773, "checksum": "4886730b20c51eece26aa392ecae2717bfe9908680419e96255351c6148eb4cc"}}, "download_size": 2016773, "post_processing_size": null, "dataset_size": 994181, "size_in_bytes": 3010954}, "plus": {"description": "    This dataset is for evaluating the performance of intent classification systems in the\n    presence of \"out-of-scope\" queries. By \"out-of-scope\", we mean queries that do not fall\n    into any of the system-supported intent classes. Most datasets include only data that is\n    \"in-scope\". Our dataset includes both in-scope and out-of-scope data. You might also know\n    the term \"out-of-scope\" by other terms, including \"out-of-domain\" or \"out-of-distribution\".\n\nOOS+, in which there are 250 out-of-scope training examples, rather than 100.\n", "citation": "    @inproceedings{larson-etal-2019-evaluation,\n    title = \"An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction\",\n    author = \"Larson, Stefan  and\n      Mahendran, Anish  and\n      Peper, Joseph J.  and\n      Clarke, Christopher  and\n      Lee, Andrew  and\n      Hill, Parker  and\n      Kummerfeld, Jonathan K.  and\n      Leach, Kevin  and\n      Laurenzano, Michael A.  and\n      Tang, Lingjia  and\n      Mars, Jason\",\n    booktitle = \"Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)\",\n    year = \"2019\",\n    url = \"https://www.aclweb.org/anthology/D19-1131\"\n}\n", "homepage": "https://github.com/clinc/oos-eval/", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "intent": {"num_classes": 151, "names": ["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"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "clinc_oos", "config_name": "plus", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 791255, "num_examples": 15250, "dataset_name": "clinc_oos"}, "validation": {"name": "validation", "num_bytes": 160302, "num_examples": 3100, "dataset_name": "clinc_oos"}, "test": {"name": "test", "num_bytes": 286970, "num_examples": 5500, "dataset_name": "clinc_oos"}}, "download_checksums": {"https://raw.githubusercontent.com/clinc/oos-eval/master/data/data_oos_plus.json": {"num_bytes": 2509789, "checksum": "bfcca9ae515623541dc1983c94c4ed7cae9d26b42ae47d74b972e51bb6f7a21f"}}, "download_size": 2509789, "post_processing_size": null, "dataset_size": 1238527, "size_in_bytes": 3748316}}

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