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Models/Doc2VecC

Doc2VecC

Reported on 10 benchmarks across 4 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing4 results

  • Sentiment AnalysisonIMDb
    Accuracy· 2017-07-08
    88.3
    best: 96.68 (RoBERTa-large with LlamBERT)
    Efficient Vector Representation for Documents through CorruptionarXiv:1707.02377
  • Sentence Pair ModelingonSICK
    MSE· 2017-07-08
    0.3053
    best: 0.2532 (Dependency Tree-LSTM (Tai et al., 2015))
    Efficient Vector Representation for Documents through CorruptionarXiv:1707.02377
  • Sentence Pair ModelingonSICK
    Pearson Correlation· 2017-07-08
    0.8381
    best: 0.8676 (Dependency Tree-LSTM (Tai et al., 2015))
    Efficient Vector Representation for Documents through CorruptionarXiv:1707.02377
  • Sentence Pair ModelingonSICK
    Spearman Correlation· 2017-07-08
    0.7621
    best: 0.8083 (Dependency Tree-LSTM (Tai et al., 2015))
    Efficient Vector Representation for Documents through CorruptionarXiv:1707.02377

Medical3 results

  • Language ModellingonSICK
    MSE· 2017-07-08
    0.3053
    best: 0.2532 (Dependency Tree-LSTM (Tai et al., 2015))
    Efficient Vector Representation for Documents through CorruptionarXiv:1707.02377
  • Language ModellingonSICK
    Pearson Correlation· 2017-07-08
    0.8381
    best: 0.8676 (Dependency Tree-LSTM (Tai et al., 2015))
    Efficient Vector Representation for Documents through CorruptionarXiv:1707.02377
  • Language ModellingonSICK
    Spearman Correlation· 2017-07-08
    0.7621
    best: 0.8083 (Dependency Tree-LSTM (Tai et al., 2015))
    Efficient Vector Representation for Documents through CorruptionarXiv:1707.02377

Methodology3 results

  • Semantic SimilarityonSICK
    MSE· 2017-07-08
    0.3053
    best: 0.2532 (Dependency Tree-LSTM (Tai et al., 2015))
    Efficient Vector Representation for Documents through CorruptionarXiv:1707.02377
  • Semantic SimilarityonSICK
    Pearson Correlation· 2017-07-08
    0.8381
    best: 0.8676 (Dependency Tree-LSTM (Tai et al., 2015))
    Efficient Vector Representation for Documents through CorruptionarXiv:1707.02377
  • Semantic SimilarityonSICK
    Spearman Correlation· 2017-07-08
    0.7621
    best: 0.8083 (Dependency Tree-LSTM (Tai et al., 2015))
    Efficient Vector Representation for Documents through CorruptionarXiv:1707.02377