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t5-base-ner-mit-restaurant

Transformers
PyTorch
English
t5
text2text-generation
ner
text generation
seq2seq
text-generation-inference
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t5-base-ner-mit-restaurant
File size: 1,767 Bytes 
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{
    "Amenity": {
        "precision": 0.6296296296296297,
        "recall": 0.6927899686520376,
        "f1-score": 0.6597014925373134,
        "support": 319.0
    },
    "Rating": {
        "precision": 0.7391304347826086,
        "recall": 0.7579617834394905,
        "f1-score": 0.7484276729559748,
        "support": 157.0
    },
    "Cuisine": {
        "precision": 0.7969924812030075,
        "recall": 0.8112244897959183,
        "f1-score": 0.8040455120101136,
        "support": 392.0
    },
    "Dish": {
        "precision": 0.7696078431372549,
        "recall": 0.7621359223300971,
        "f1-score": 0.7658536585365854,
        "support": 206.0
    },
    "Hours": {
        "precision": 0.6326530612244898,
        "recall": 0.75,
        "f1-score": 0.6863468634686347,
        "support": 124.0
    },
    "Location": {
        "precision": 0.8348968105065666,
        "recall": 0.7974910394265233,
        "f1-score": 0.8157653528872595,
        "support": 558.0
    },
    "Price": {
        "precision": 0.8461538461538461,
        "recall": 0.8461538461538461,
        "f1-score": 0.8461538461538461,
        "support": 117.0
    },
    "Restaurant_Name": {
        "precision": 0.8160535117056856,
        "recall": 0.8160535117056856,
        "f1-score": 0.8160535117056856,
        "support": 299.0
    },
    "macro_avg": {
        "precision": 0.7581397022928861,
        "recall": 0.7792263201879498,
        "f1-score": 0.7677934887819267
    },
    "micro_avg": {
        "precision": 0.7808471454880295,
        "recall": 0.7808471454880295,
        "f1-score": 0.7808471454880295
    },
    "weighted_avg": {
        "precision": 0.771260128123884,
        "recall": 0.7808471454880295,
        "f1-score": 0.7754160649729253
    }
}