xed_en_fi

อ้างอิง:

• รหัส
• กอดหน้า

en_คำอธิบายประกอบ

ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:

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

• คำอธิบาย :

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.

• ใบอนุญาต : ใบอนุญาต: Creative Commons Attribution 4.0 ใบอนุญาตสากล (CC-BY)
• เวอร์ชั่น : 1.1.0
• แยก :

• คุณสมบัติ :

{
    "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_เป็นกลาง

ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:

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

• คำอธิบาย :

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.

• ใบอนุญาต : ใบอนุญาต: Creative Commons Attribution 4.0 ใบอนุญาตสากล (CC-BY)
• เวอร์ชั่น : 1.1.0
• แยก :

• คุณสมบัติ :

{
    "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_คำอธิบายประกอบ

ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:

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

• คำอธิบาย :

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.

• ใบอนุญาต : ใบอนุญาต: Creative Commons Attribution 4.0 ใบอนุญาตสากล (CC-BY)
• เวอร์ชั่น : 1.1.0
• แยก :

• คุณสมบัติ :

{
    "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_เป็นกลาง

ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:

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

• คำอธิบาย :

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.

• ใบอนุญาต : ใบอนุญาต: Creative Commons Attribution 4.0 ใบอนุญาตสากล (CC-BY)
• เวอร์ชั่น : 1.1.0
• แยก :

• คุณสมบัติ :

{
    "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"
    }
}