xglue

Riferimenti:

ner

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:xglue/ner')
  • Descrizione :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licenza : nessuna licenza conosciuta
  • Versione : 1.0.0
  • Divide :
Diviso Esempi
'test.de' 3007
'test.en' 3454
'test.es' 1523
'test.nl' 5202
'train' 14042
'validation.de' 2874
'validation.en' 3252
'validation.es' 1923
'validation.nl' 2895
  • Caratteristiche :
{
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "num_classes": 9,
            "names": [
                "O",
                "B-PER",
                "I-PER",
                "B-ORG",
                "I-ORG",
                "B-LOC",
                "I-LOC",
                "B-MISC",
                "I-MISC"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

pos

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:xglue/pos')
  • Descrizione :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licenza : nessuna licenza conosciuta
  • Versione : 1.0.0
  • Divide :
Diviso Esempi
'test.ar' 679
'test.bg' 1115
'test.de' 976
'test.el' 455
'test.en' 2076
'test.es' 425
'test.fr' 415
'test.hi' 1683
'test.it' 481
'test.nl' 595
'test.pl' 2214
'test.ru' 600
'test.th' 497
'test.tr' 982
'test.ur' 534
'test.vi' 799
'test.zh' 499
'train' 25376
'validation.ar' 908
'validation.bg' 1114
'validation.de' 798
'validation.el' 402
'validation.en' 2001
'validation.es' 1399
'validation.fr' 1475
'validation.hi' 1658
'validation.it' 563
'validation.nl' 717
'validation.pl' 2214
'validation.ru' 578
'validation.th' 497
'validation.tr' 987
'validation.ur' 551
'validation.vi' 799
'validation.zh' 499
  • Caratteristiche :
{
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "pos": {
        "feature": {
            "num_classes": 17,
            "names": [
                "ADJ",
                "ADP",
                "ADV",
                "AUX",
                "CCONJ",
                "DET",
                "INTJ",
                "NOUN",
                "NUM",
                "PART",
                "PRON",
                "PROPN",
                "PUNCT",
                "SCONJ",
                "SYM",
                "VERB",
                "X"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

mlqa

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:xglue/mlqa')
  • Descrizione :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licenza : nessuna licenza conosciuta
  • Versione : 1.0.0
  • Divide :
Diviso Esempi
'test.ar' 5335
'test.de' 4517
'test.en' 11590
'test.es' 5253
'test.hi' 4918
'test.vi' 5495
'test.zh' 5137
'train' 87599
'validation.ar' 517
'validation.de' 512
'validation.en' 1148
'validation.es' 500
'validation.hi' 507
'validation.vi' 511
'validation.zh' 504
  • Caratteristiche :
{
    "context": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answers": {
        "feature": {
            "answer_start": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "text": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            }
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

nc

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:xglue/nc')
  • Descrizione :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licenza : nessuna licenza conosciuta
  • Versione : 1.0.0
  • Divide :
Diviso Esempi
'test.de' 10000
'test.en' 10000
'test.es' 10000
'test.fr' 10000
'test.ru' 10000
'train' 100000
'validation.de' 10000
'validation.en' 10000
'validation.es' 10000
'validation.fr' 10000
'validation.ru' 10000
  • Caratteristiche :
{
    "news_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "news_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "news_category": {
        "num_classes": 10,
        "names": [
            "foodanddrink",
            "sports",
            "travel",
            "finance",
            "lifestyle",
            "news",
            "entertainment",
            "health",
            "video",
            "autos"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

xnli

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:xglue/xnli')
  • Descrizione :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licenza : nessuna licenza conosciuta
  • Versione : 1.0.0
  • Divide :
Diviso Esempi
'test.ar' 5010
'test.bg' 5010
'test.de' 5010
'test.el' 5010
'test.en' 5010
'test.es' 5010
'test.fr' 5010
'test.hi' 5010
'test.ru' 5010
'test.sw' 5010
'test.th' 5010
'test.tr' 5010
'test.ur' 5010
'test.vi' 5010
'test.zh' 5010
'train' 392702
'validation.ar' 2490
'validation.bg' 2490
'validation.de' 2490
'validation.el' 2490
'validation.en' 2490
'validation.es' 2490
'validation.fr' 2490
'validation.hi' 2490
'validation.ru' 2490
'validation.sw' 2490
'validation.th' 2490
'validation.tr' 2490
'validation.ur' 2490
'validation.vi' 2490
'validation.zh' 2490
  • Caratteristiche :
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "hypothesis": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 3,
        "names": [
            "entailment",
            "neutral",
            "contradiction"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

zampe-x

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:xglue/paws-x')
  • Descrizione :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licenza : nessuna licenza conosciuta
  • Versione : 1.0.0
  • Divide :
Diviso Esempi
'test.de' 2000
'test.en' 2000
'test.es' 2000
'test.fr' 2000
'train' 49401
'validation.de' 2000
'validation.en' 2000
'validation.es' 2000
'validation.fr' 2000
  • Caratteristiche :
{
    "sentence1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "different",
            "same"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

qadsm

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:xglue/qadsm')
  • Descrizione :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licenza : nessuna licenza conosciuta
  • Versione : 1.0.0
  • Divide :
Diviso Esempi
'test.de' 10000
'test.en' 10000
'test.fr' 10000
'train' 100000
'validation.de' 10000
'validation.en' 10000
'validation.fr' 10000
  • Caratteristiche :
{
    "query": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "ad_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "ad_description": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "relevance_label": {
        "num_classes": 2,
        "names": [
            "Bad",
            "Good"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

wpr

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:xglue/wpr')
  • Descrizione :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licenza : nessuna licenza conosciuta
  • Versione : 1.0.0
  • Divide :
Diviso Esempi
'test.de' 9997
'test.en' 10004
'test.es' 10006
'test.fr' 10020
'test.it' 10001
'test.pt' 10015
'test.zh' 9999
'train' 99997
'validation.de' 10004
'validation.en' 10008
'validation.es' 10004
'validation.fr' 10005
'validation.it' 10003
'validation.pt' 10001
'validation.zh' 10002
  • Caratteristiche :
{
    "query": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "web_page_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "web_page_snippet": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "relavance_label": {
        "num_classes": 5,
        "names": [
            "Bad",
            "Fair",
            "Good",
            "Excellent",
            "Perfect"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

qam

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:xglue/qam')
  • Descrizione :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licenza : nessuna licenza conosciuta
  • Versione : 1.0.0
  • Divide :
Diviso Esempi
'test.de' 10000
'test.en' 10000
'test.fr' 10000
'train' 100000
'validation.de' 10000
'validation.en' 10000
'validation.fr' 10000
  • Caratteristiche :
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "False",
            "True"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

qg

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:xglue/qg')
  • Descrizione :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licenza : nessuna licenza conosciuta
  • Versione : 1.0.0
  • Divide :
Diviso Esempi
'test.de' 10000
'test.en' 10000
'test.es' 10000
'test.fr' 10000
'test.it' 10000
'test.pt' 10000
'train' 100000
'validation.de' 10000
'validation.en' 10000
'validation.es' 10000
'validation.fr' 10000
'validation.it' 10000
'validation.pt' 10000
  • Caratteristiche :
{
    "answer_passage": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

ntg

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:xglue/ntg')
  • Descrizione :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licenza : nessuna licenza conosciuta
  • Versione : 1.0.0
  • Divide :
Diviso Esempi
'test.de' 10000
'test.en' 10000
'test.es' 10000
'test.fr' 10000
'test.ru' 10000
'train' 300000
'validation.de' 10000
'validation.en' 10000
'validation.es' 10000
'validation.fr' 10000
'validation.ru' 10000
  • Caratteristiche :
{
    "news_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "news_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}