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cross-encoder-bert-base-fr-v1

Text Classification
Transformers
Safetensors
sentence-transformers
French
bert
cross-encoder
text-embeddings-inference
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Model Details

Model Description

This is a specialized cross encoder designed for French language tasks. It is based on Google's BERT (bert-base-multilingual-cased) architecture and fine-tuned on the PhilipMay/stsb_multi_mt French dataset. After 10 epochs of training, the model achieved a Pearson correlation of 0.83621 and a Spearman correlation of 0.82456 on the STS-B test set.

  • Developed by: Leviatan Research Team
  • Model type: Cross Encoder
  • Language(s) (NLP): French
  • Finetuned from model [optional]: Google's BERT (bert-base-multilingual-cased)

Results

  • STS-B Test Set:

    • Metric: CECorrelationEvaluator
      • Pearson: 0.83621
      • Spearman: 0.82456

  • Zero-Shot Test using FQuAD as Knowledge Base:

    • Number of questions tested: 3188
    • Number of documents considered: 768
    • Top 5 k@precision: 0.8563
    • Top 5 MRR: 0.6898

  • Comparison with dangvantuan/CrossEncoder-camembert-large:

    • Top 5 k@precision: 0.6688
    • Top 5 MRR: 0.4131
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