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{
  "default": {
    "description": "AfriSenti is the largest sentiment analysis benchmark for under-represented languages---covering 110,000+ annotated tweets in 14 African languages (Amharic, Algerian Arabic, Hausa, Igbo, Kinyarwanda, Moroccan Arabic, Mozambican Portuguese, Nigerian Pidgin, Oromo, Swahili, Tigrinya, Twi, Xitsonga, and Yoruba) from four language families (Afro-Asiatic, English Creole, Indo-European and Niger-Congo).\n",
    "citation": " ",
    "homepage": "https://github.com/afrisenti-semeval/afrisent-semeval-2023",
    "license": "",
    "features": {
      "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
      },
      "label": {
        "num_classes": 3,
        "names": [
          "positive",
          "negative",
          "neutral"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
      }
    },
    "post_processed": null,
    "supervised_keys": {
      "input": "tweet",
      "output": "label"
    },
    "task_templates": [
      {
        "task": "text-classification",
        "text_column": "tweet",
        "label_column": "label",
        "labels": [
          "positive",
          "negative",
          "neutral"
        ]
      }
    ],
    "builder_name": "AfriSenti",
    "config_name": "default",
    "version": {
      "version_str": "0.0.0",
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      "major": 0,
      "minor": 0,
      "patch": 0
  
    },
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}