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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: 1,454 Bytes 
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{
  "dataset_revision": "66e76a618a34d6d565d5538088562851e6daa7ec",
  "mteb_dataset_name": "Ocnli",
  "mteb_version": "1.1.2",
  "validation": {
    "cos_sim": {
      "accuracy": 0.8110449377368706,
      "accuracy_threshold": 0.5926690697669983,
      "ap": 0.851744999044347,
      "f1": 0.8298479087452472,
      "f1_threshold": 0.5656208992004395,
      "precision": 0.7545375972342264,
      "recall": 0.9218585005279831
    },
    "dot": {
      "accuracy": 0.8110449377368706,
      "accuracy_threshold": 0.5926690697669983,
      "ap": 0.851744999044347,
      "f1": 0.8298479087452472,
      "f1_threshold": 0.5656208992004395,
      "precision": 0.7545375972342264,
      "recall": 0.9218585005279831
    },
    "euclidean": {
      "accuracy": 0.8110449377368706,
      "accuracy_threshold": 0.9025861024856567,
      "ap": 0.851744999044347,
      "f1": 0.8298479087452472,
      "f1_threshold": 0.9320720434188843,
      "precision": 0.7545375972342264,
      "recall": 0.9218585005279831
    },
    "evaluation_time": 4.07,
    "manhattan": {
      "accuracy": 0.8105035192203573,
      "accuracy_threshold": 30.224245071411133,
      "ap": 0.8514000324074237,
      "f1": 0.8296155671570954,
      "f1_threshold": 31.517192840576172,
      "precision": 0.753448275862069,
      "recall": 0.9229144667370645
    },
    "max": {
      "accuracy": 0.8110449377368706,
      "ap": 0.851744999044347,
      "f1": 0.8298479087452472
    }
  }
}