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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: 1,457 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": 0.6553086042404175,
      "ap": 0.9049178248661934,
      "f1": 0.8428475486903962,
      "f1_threshold": 0.6404943466186523,
      "precision": 0.8084603822203135,
      "recall": 0.8802899228431144
    },
    "dot": {
      "accuracy": 0.8343956704750451,
      "accuracy_threshold": 0.6553086042404175,
      "ap": 0.904952509998683,
      "f1": 0.8428475486903962,
      "f1_threshold": 0.6404944658279419,
      "precision": 0.8084603822203135,
      "recall": 0.8802899228431144
    },
    "euclidean": {
      "accuracy": 0.8343956704750451,
      "accuracy_threshold": 0.8302907943725586,
      "ap": 0.904917738313486,
      "f1": 0.8428475486903962,
      "f1_threshold": 0.8479452133178711,
      "precision": 0.8084603822203135,
      "recall": 0.8802899228431144
    },
    "evaluation_time": 17.58,
    "manhattan": {
      "accuracy": 0.8354780517137703,
      "accuracy_threshold": 28.025470733642578,
      "ap": 0.9048077217839686,
      "f1": 0.8443433769187039,
      "f1_threshold": 28.200302124023438,
      "precision": 0.8218238158477202,
      "recall": 0.8681318681318682
    },
    "max": {
      "accuracy": 0.8354780517137703,
      "ap": 0.904952509998683,
      "f1": 0.8443433769187039
    }
  }
}