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Models/BERT-PT

BERT-PT

Reported on 12 benchmarks across 2 tasks · 1 paper · 6 SOTA

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

Natural Language Processing14 results

  • Sentiment AnalysisonSemEval-2014 Task-4
    Restaurant (Acc)· uses extra data· 2019-04-03
    84.95
    best: 8946 (ABSA-DeBERTa)
    SOTA
    BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment AnalysisarXiv:1904.02232
  • Sentiment AnalysisonSemEval 2014 Task 4 Sub Task 1
    Laptop (F1)· 2019-04-03
    84.26
    best: 92.3 (InstructABSA)
    SOTA
    BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment AnalysisarXiv:1904.02232
  • Sentiment AnalysisonSemEval 2014 Task 4 Sub Task 1
    Restaurant (F1)· 2019-04-03
    77.97
    best: 92.76 (InstructABSA)
    SOTA
    BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment AnalysisarXiv:1904.02232
  • Aspect-Based Sentiment Analysis (ABSA)onSemEval-2014 Task-4
    Restaurant (Acc)· uses extra data· 2019-04-03
    84.95
    best: 8946 (ABSA-DeBERTa)
    SOTA
    BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment AnalysisarXiv:1904.02232
  • Aspect-Based Sentiment Analysis (ABSA)onSemEval 2014 Task 4 Sub Task 1
    Laptop (F1)· 2019-04-03
    84.26
    best: 92.3 (InstructABSA)
    SOTA
    BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment AnalysisarXiv:1904.02232
  • Aspect-Based Sentiment Analysis (ABSA)onSemEval 2014 Task 4 Sub Task 1
    Restaurant (F1)· 2019-04-03
    77.97
    best: 92.76 (InstructABSA)
    SOTA
    BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment AnalysisarXiv:1904.02232
  • Sentiment AnalysisonSemEval-2014 Task-4
    Laptop (Acc)· uses extra data· 2019-04-03
    78.07
    best: 8276 (ABSA-DeBERTa)
    BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment AnalysisarXiv:1904.02232
  • Sentiment AnalysisonSemEval-2014 Task-4
    Mean Acc (Restaurant + Laptop)· uses extra data· 2019-04-03
    81.51
    best: 8611 (ABSA-DeBERTa)
    BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment AnalysisarXiv:1904.02232
  • Aspect-Based Sentiment Analysis (ABSA)onSemEval-2014 Task-4
    Laptop (Acc)· uses extra data· 2019-04-03
    78.07
    best: 8276 (ABSA-DeBERTa)
    BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment AnalysisarXiv:1904.02232
  • Aspect-Based Sentiment Analysis (ABSA)onSemEval-2014 Task-4
    Mean Acc (Restaurant + Laptop)· uses extra data· 2019-04-03
    81.51
    best: 8611 (ABSA-DeBERTa)
    BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment AnalysisarXiv:1904.02232
  • Sentiment AnalysisonFABSA
    F1 (%)
    78.8
    best: 80.9 (DeBERTa-pair-large)
  • Sentiment AnalysisonFABSA
    F1 (%)
    78.8
    best: 80.9 (DeBERTa-pair-large)
  • Aspect-Based Sentiment Analysis (ABSA)onFABSA
    F1 (%)
    78.8
    best: 80.9 (DeBERTa-pair-large)
  • Aspect-Based Sentiment Analysis (ABSA)onFABSA
    F1 (%)
    78.8
    best: 80.9 (DeBERTa-pair-large)