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Ammar-alhaj-ali
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arabic-MARBERT-dialect-identification-city

Text Classification
Transformers
PyTorch
Arabic
bert
text classification
Inference Endpoints
Model card Files Community
1
arabic-MARBERT-dialect-identification-city
File size: 1,917 Bytes 
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{
  "_name_or_path": "UBC-NLP/MARBERT",
  "architectures": [
    "BertForSequenceClassification"
  ],
  "attention_probs_dropout_prob": 0.1,
  "classifier_dropout": null,
  "directionality": "bidi",
  "gradient_checkpointing": false,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.1,
  "hidden_size": 768,
  "id2label": {
    "0": "Jerusalem",
    "1": "Tunis",
    "2": "Mosul",
    "3": "Sfax",
    "4": "Rabat",
    "5": "Basra",
    "6": "Muscat",
    "7": "Khartoum",
    "8": "Amman",
    "9": "Sanaa",
    "10": "Baghdad",
    "11": "Jeddah",
    "12": "Cairo",
    "13": "Algiers",
    "14": "Alexandria",
    "15": "Aleppo",
    "16": "Fes",
    "17": "Beirut",
    "18": "Tripoli",
    "19": "Doha",
    "20": "MSA",
    "21": "Riyadh",
    "22": "Salt",
    "23": "Damascus",
    "24": "Aswan",
    "25": "Benghazi"
  },
  "initializer_range": 0.02,
  "intermediate_size": 3072,
  "label2id": {
    "Jerusalem": 0,
    "Tunis": 1,
    "Mosul": 2,
    "Sfax": 3,
    "Rabat": 4,
    "Basra": 5,
    "Muscat": 6,
    "Khartoum": 7,
    "Amman": 8,
    "Sanaa": 9,
    "Baghdad": 10,
    "Jeddah": 11,
    "Cairo": 12,
    "Algiers": 13,
    "Alexandria": 14,
    "Aleppo": 15,
    "Fes": 16,
    "Beirut": 17,
    "Tripoli": 18,
    "Doha": 19,
    "MSA": 20,
    "Riyadh": 21,
    "Salt": 22,
    "Damascus": 23,
    "Aswan": 24,
    "Benghazi": 25
  },
  "layer_norm_eps": 1e-12,
  "max_position_embeddings": 512,
  "model_type": "bert",
  "num_attention_heads": 12,
  "num_hidden_layers": 12,
  "pad_token_id": 0,
  "pooler_fc_size": 768,
  "pooler_num_attention_heads": 12,
  "pooler_num_fc_layers": 3,
  "pooler_size_per_head": 128,
  "pooler_type": "first_token_transform",
  "position_embedding_type": "absolute",
  "problem_type": "single_label_classification",
  "torch_dtype": "float32",
  "transformers_version": "4.20.1",
  "type_vocab_size": 2,
  "use_cache": true,
  "vocab_size": 100000
}