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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: 1,417 Bytes 
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{
  "dataset_revision": null,
  "mteb_dataset_name": "Ocnli",
  "mteb_version": "1.1.1",
  "validation": {
    "cos_sim": {
      "accuracy": 0.8110449377368706,
      "accuracy_threshold": 0.5930440425872803,
      "ap": 0.8516262845422288,
      "f1": 0.8297771455666192,
      "f1_threshold": 0.5647917985916138,
      "precision": 0.7530120481927711,
      "recall": 0.9239704329461457
    },
    "dot": {
      "accuracy": 0.8110449377368706,
      "accuracy_threshold": 0.5982565879821777,
      "ap": 0.8511448381714821,
      "f1": 0.8299190090519295,
      "f1_threshold": 0.5676579475402832,
      "precision": 0.7560763888888888,
      "recall": 0.9197465681098205
    },
    "euclidean": {
      "accuracy": 0.8105035192203573,
      "accuracy_threshold": 0.8990259170532227,
      "ap": 0.8516821622996872,
      "f1": 0.8300094966761632,
      "f1_threshold": 0.9317486882209778,
      "precision": 0.7540983606557377,
      "recall": 0.9229144667370645
    },
    "evaluation_time": 1.5,
    "manhattan": {
      "accuracy": 0.8115863562533838,
      "accuracy_threshold": 30.2585506439209,
      "ap": 0.8514921863839019,
      "f1": 0.8291048348492102,
      "f1_threshold": 31.238189697265625,
      "precision": 0.7583187390542907,
      "recall": 0.914466737064414
    },
    "max": {
      "accuracy": 0.8115863562533838,
      "ap": 0.8516821622996872,
      "f1": 0.8300094966761632
    }
  }
}