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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: 1,441 Bytes 
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{
  "dataset_revision": "41bc36f332156f7adc9e38f53777c959b2ae9766",
  "mteb_dataset_name": "Cmnli",
  "mteb_version": "1.1.2",
  "validation": {
    "cos_sim": {
      "accuracy": 0.8343956704750451,
      "accuracy_threshold": 0.6553230459269956,
      "ap": 0.9049177266479603,
      "f1": 0.8428475486903962,
      "f1_threshold": 0.6404635431235377,
      "precision": 0.8084603822203135,
      "recall": 0.8802899228431144
    },
    "dot": {
      "accuracy": 0.8342754058929646,
      "accuracy_threshold": 0.65576171875,
      "ap": 0.9045598531097172,
      "f1": 0.842911877394636,
      "f1_threshold": 0.64453125,
      "precision": 0.8135740700456819,
      "recall": 0.8744447042319383
    },
    "euclidean": {
      "accuracy": 0.8343956704750451,
      "accuracy_threshold": 0.8300989242334467,
      "ap": 0.904917028881393,
      "f1": 0.8427884077430905,
      "f1_threshold": 0.8482995473168584,
      "precision": 0.8081545064377682,
      "recall": 0.8805237315875614
    },
    "evaluation_time": 7.24,
    "manhattan": {
      "accuracy": 0.8354780517137703,
      "accuracy_threshold": 28.19183760881424,
      "ap": 0.904805294463615,
      "f1": 0.8444393904935183,
      "f1_threshold": 28.19183760881424,
      "precision": 0.8220057560327652,
      "recall": 0.8681318681318682
    },
    "max": {
      "accuracy": 0.8354780517137703,
      "ap": 0.9049177266479603,
      "f1": 0.8444393904935183
    }
  }
}