xed_en_fi

הפניות:

• קוד
• מחבקת פנים

en_מבוער

השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:

ds = tfds.load('huggingface:xed_en_fi/en_annotated')

• תיאור :

A multilingual fine-grained emotion dataset. The dataset consists of human annotated Finnish (25k) and English sentences (30k). Plutchik’s
core emotions are used to annotate the dataset with the addition of neutral to create a multilabel multiclass
dataset. The dataset is carefully evaluated using language-specific BERT models and SVMs to
show that XED performs on par with other similar datasets and is therefore a useful tool for
sentiment analysis and emotion detection.

• רישיון : רישיון: Creative Commons Attribution 4.0 רישיון בינלאומי (CC-BY)
• גרסה : 1.1.0
• פיצולים :

• מאפיינים :

{
    "sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "labels": {
        "feature": {
            "num_classes": 9,
            "names": [
                "neutral",
                "anger",
                "anticipation",
                "disgust",
                "fear",
                "joy",
                "sadness",
                "surprise",
                "trust"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

en_ניטרלי

השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:

ds = tfds.load('huggingface:xed_en_fi/en_neutral')

• תיאור :

A multilingual fine-grained emotion dataset. The dataset consists of human annotated Finnish (25k) and English sentences (30k). Plutchik’s
core emotions are used to annotate the dataset with the addition of neutral to create a multilabel multiclass
dataset. The dataset is carefully evaluated using language-specific BERT models and SVMs to
show that XED performs on par with other similar datasets and is therefore a useful tool for
sentiment analysis and emotion detection.

• רישיון : רישיון: Creative Commons Attribution 4.0 רישיון בינלאומי (CC-BY)
• גרסה : 1.1.0
• פיצולים :

• מאפיינים :

{
    "sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "labels": {
        "num_classes": 9,
        "names": [
            "neutral",
            "anger",
            "anticipation",
            "disgust",
            "fear",
            "joy",
            "sadness",
            "surprise",
            "trust"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

fi_בואר

השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:

ds = tfds.load('huggingface:xed_en_fi/fi_annotated')

• תיאור :

A multilingual fine-grained emotion dataset. The dataset consists of human annotated Finnish (25k) and English sentences (30k). Plutchik’s
core emotions are used to annotate the dataset with the addition of neutral to create a multilabel multiclass
dataset. The dataset is carefully evaluated using language-specific BERT models and SVMs to
show that XED performs on par with other similar datasets and is therefore a useful tool for
sentiment analysis and emotion detection.

• רישיון : רישיון: Creative Commons Attribution 4.0 רישיון בינלאומי (CC-BY)
• גרסה : 1.1.0
• פיצולים :

• מאפיינים :

{
    "sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "labels": {
        "feature": {
            "num_classes": 9,
            "names": [
                "neutral",
                "anger",
                "anticipation",
                "disgust",
                "fear",
                "joy",
                "sadness",
                "surprise",
                "trust"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

fi_neutral

השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:

ds = tfds.load('huggingface:xed_en_fi/fi_neutral')

• תיאור :

A multilingual fine-grained emotion dataset. The dataset consists of human annotated Finnish (25k) and English sentences (30k). Plutchik’s
core emotions are used to annotate the dataset with the addition of neutral to create a multilabel multiclass
dataset. The dataset is carefully evaluated using language-specific BERT models and SVMs to
show that XED performs on par with other similar datasets and is therefore a useful tool for
sentiment analysis and emotion detection.

• רישיון : רישיון: Creative Commons Attribution 4.0 רישיון בינלאומי (CC-BY)
• גרסה : 1.1.0
• פיצולים :

• מאפיינים :

{
    "sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "labels": {
        "num_classes": 9,
        "names": [
            "neutral",
            "anger",
            "anticipation",
            "disgust",
            "fear",
            "joy",
            "sadness",
            "surprise",
            "trust"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}