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acge_text_embedding

Sentence Similarity
sentence-transformers
PyTorch
Safetensors
bert
mteb
feature-extraction
Eval Results
text-embeddings-inference
Inference Endpoints
Model card Files Community
16
acge_text_embedding
File size: 1,456 Bytes 
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{
  "dataset_revision": "41bc36f332156f7adc9e38f53777c959b2ae9766",
  "mteb_dataset_name": "Cmnli",
  "mteb_version": "1.1.2",
  "validation": {
    "cos_sim": {
      "accuracy": 0.834155141310884,
      "accuracy_threshold": 0.6564782857894897,
      "ap": 0.9049006000181046,
      "f1": 0.8428797826579125,
      "f1_threshold": 0.6480306386947632,
      "precision": 0.8169848584595129,
      "recall": 0.8704699555763385
    },
    "dot": {
      "accuracy": 0.8340348767288034,
      "accuracy_threshold": 0.6529912352561951,
      "ap": 0.9050667776818787,
      "f1": 0.8431853669417801,
      "f1_threshold": 0.6381836533546448,
      "precision": 0.8061420345489443,
      "recall": 0.88379705400982
    },
    "euclidean": {
      "accuracy": 0.8343956704750451,
      "accuracy_threshold": 0.8326233625411987,
      "ap": 0.9048869698176196,
      "f1": 0.8432616081540204,
      "f1_threshold": 0.8387479186058044,
      "precision": 0.8177026136613222,
      "recall": 0.8704699555763385
    },
    "evaluation_time": 13.31,
    "manhattan": {
      "accuracy": 0.8355983162958509,
      "accuracy_threshold": 28.043197631835938,
      "ap": 0.9047972486190912,
      "f1": 0.8442325158946412,
      "f1_threshold": 28.235897064208984,
      "precision": 0.820569410726109,
      "recall": 0.8693009118541033
    },
    "max": {
      "accuracy": 0.8355983162958509,
      "ap": 0.9050667776818787,
      "f1": 0.8442325158946412
    }
  }
}