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TextAttack Model Zoo

More details at https://textattack.readthedocs.io/en/latest/3recipes/models.html

TextAttack includes pre-trained models for different common NLP tasks. This makes it easier for users to get started with TextAttack. It also enables a more fair comparison of attacks from the literature.

All evaluation results were obtained using textattack eval to evaluate models on their default test dataset (test set, if labels are available, otherwise, eval/validation set). You can use this command to verify the accuracies for yourself: for example, textattack eval --model roberta-base-mr.

The LSTM and wordCNN models' code is available in textattack.models.helpers. All other models are transformers imported from the transformers package. To list evaluate all TextAttack pretrained models, invoke textattack eval without specifying a model: textattack eval --num-examples 1000. All evaluations shown are on the full validation or test set up to 1000 examples.

LSTM

  • AG News (lstm-ag-news)
    • datasets dataset ag_news, split test
      • Correct/Whole: 914/1000
      • Accuracy: 91.4%
  • IMDB (lstm-imdb)
    • datasets dataset imdb, split test
      • Correct/Whole: 883/1000
      • Accuracy: 88.30%
  • Movie Reviews [Rotten Tomatoes] (lstm-mr)
    • datasets dataset rotten_tomatoes, split validation
      • Correct/Whole: 807/1000
      • Accuracy: 80.70%
    • datasets dataset rotten_tomatoes, split test
      • Correct/Whole: 781/1000
      • Accuracy: 78.10%
  • SST-2 (lstm-sst2)
    • datasets dataset glue, subset sst2, split validation
      • Correct/Whole: 737/872
      • Accuracy: 84.52%
  • Yelp Polarity (lstm-yelp)
    • datasets dataset yelp_polarity, split test
      • Correct/Whole: 922/1000
      • Accuracy: 92.20%

wordCNN

  • AG News (cnn-ag-news)
    • datasets dataset ag_news, split test
      • Correct/Whole: 910/1000
      • Accuracy: 91.00%
  • IMDB (cnn-imdb)
    • datasets dataset imdb, split test
      • Correct/Whole: 863/1000
      • Accuracy: 86.30%
  • Movie Reviews [Rotten Tomatoes] (cnn-mr)
    • datasets dataset rotten_tomatoes, split validation
      • Correct/Whole: 794/1000
      • Accuracy: 79.40%
    • datasets dataset rotten_tomatoes, split test
      • Correct/Whole: 768/1000
      • Accuracy: 76.80%
  • SST-2 (cnn-sst2)
    • datasets dataset glue, subset sst2, split validation
      • Correct/Whole: 721/872
      • Accuracy: 82.68%
  • Yelp Polarity (cnn-yelp)
    • datasets dataset yelp_polarity, split test
      • Correct/Whole: 913/1000
      • Accuracy: 91.30%

albert-base-v2

  • AG News (albert-base-v2-ag-news)
    • datasets dataset ag_news, split test
      • Correct/Whole: 943/1000
      • Accuracy: 94.30%
  • CoLA (albert-base-v2-cola)
    • datasets dataset glue, subset cola, split validation
      • Correct/Whole: 829/1000
      • Accuracy: 82.90%
  • IMDB (albert-base-v2-imdb)
    • datasets dataset imdb, split test
      • Correct/Whole: 913/1000
      • Accuracy: 91.30%
  • Movie Reviews [Rotten Tomatoes] (albert-base-v2-mr)
    • datasets dataset rotten_tomatoes, split validation
      • Correct/Whole: 882/1000
      • Accuracy: 88.20%
    • datasets dataset rotten_tomatoes, split test
      • Correct/Whole: 851/1000
      • Accuracy: 85.10%
  • Quora Question Pairs (albert-base-v2-qqp)
    • datasets dataset glue, subset qqp, split validation
      • Correct/Whole: 914/1000
      • Accuracy: 91.40%
  • Recognizing Textual Entailment (albert-base-v2-rte)
    • datasets dataset glue, subset rte, split validation
      • Correct/Whole: 211/277
      • Accuracy: 76.17%
  • SNLI (albert-base-v2-snli)
    • datasets dataset snli, split test
      • Correct/Whole: 883/1000
      • Accuracy: 88.30%
  • SST-2 (albert-base-v2-sst2)
    • datasets dataset glue, subset sst2, split validation
      • Correct/Whole: 807/872
      • Accuracy: 92.55%)
  • STS-b (albert-base-v2-stsb)
    • datasets dataset glue, subset stsb, split validation
    • Pearson correlation: 0.9041359738552746
    • Spearman correlation: 0.8995912861209745
  • WNLI (albert-base-v2-wnli)
    • datasets dataset glue, subset wnli, split validation
      • Correct/Whole: 42/71
      • Accuracy: 59.15%
  • Yelp Polarity (albert-base-v2-yelp)
    • datasets dataset yelp_polarity, split test
      • Correct/Whole: 963/1000
      • Accuracy: 96.30%

bert-base-uncased

  • AG News (bert-base-uncased-ag-news)
    • datasets dataset ag_news, split test
      • Correct/Whole: 942/1000
      • Accuracy: 94.20%
  • CoLA (bert-base-uncased-cola)
    • datasets dataset glue, subset cola, split validation
      • Correct/Whole: 812/1000
      • Accuracy: 81.20%
  • IMDB (bert-base-uncased-imdb)
    • datasets dataset imdb, split test
      • Correct/Whole: 919/1000
      • Accuracy: 91.90%
  • MNLI matched (bert-base-uncased-mnli)
    • datasets dataset glue, subset mnli, split validation_matched
      • Correct/Whole: 840/1000
      • Accuracy: 84.00%
  • Movie Reviews [Rotten Tomatoes] (bert-base-uncased-mr)
    • datasets dataset rotten_tomatoes, split validation
      • Correct/Whole: 876/1000
      • Accuracy: 87.60%
    • datasets dataset rotten_tomatoes, split test
      • Correct/Whole: 838/1000
      • Accuracy: 83.80%
  • MRPC (bert-base-uncased-mrpc)
    • datasets dataset glue, subset mrpc, split validation
      • Correct/Whole: 358/408
      • Accuracy: 87.75%
  • QNLI (bert-base-uncased-qnli)
    • datasets dataset glue, subset qnli, split validation
      • Correct/Whole: 904/1000
      • Accuracy: 90.40%
  • Quora Question Pairs (bert-base-uncased-qqp)
    • datasets dataset glue, subset qqp, split validation
      • Correct/Whole: 924/1000
      • Accuracy: 92.40%
  • Recognizing Textual Entailment (bert-base-uncased-rte)
    • datasets dataset glue, subset rte, split validation
      • Correct/Whole: 201/277
      • Accuracy: 72.56%
  • SNLI (bert-base-uncased-snli)
    • datasets dataset snli, split test
      • Correct/Whole: 894/1000
      • Accuracy: 89.40%
  • SST-2 (bert-base-uncased-sst2)
    • datasets dataset glue, subset sst2, split validation
      • Correct/Whole: 806/872
      • Accuracy: 92.43%)
  • STS-b (bert-base-uncased-stsb)
    • datasets dataset glue, subset stsb, split validation
    • Pearson correlation: 0.8775458937815515
    • Spearman correlation: 0.8773251339980935
  • WNLI (bert-base-uncased-wnli)
    • datasets dataset glue, subset wnli, split validation
      • Correct/Whole: 40/71
      • Accuracy: 56.34%
  • Yelp Polarity (bert-base-uncased-yelp)
    • datasets dataset yelp_polarity, split test
      • Correct/Whole: 963/1000
      • Accuracy: 96.30%

distilbert-base-cased

  • CoLA (distilbert-base-cased-cola)
    • datasets dataset glue, subset cola, split validation
      • Correct/Whole: 786/1000
      • Accuracy: 78.60%
  • MRPC (distilbert-base-cased-mrpc)
    • datasets dataset glue, subset mrpc, split validation
      • Correct/Whole: 320/408
      • Accuracy: 78.43%
  • Quora Question Pairs (distilbert-base-cased-qqp)
    • datasets dataset glue, subset qqp, split validation
      • Correct/Whole: 908/1000
      • Accuracy: 90.80%
  • SNLI (distilbert-base-cased-snli)
    • datasets dataset snli, split test
      • Correct/Whole: 861/1000
      • Accuracy: 86.10%
  • SST-2 (distilbert-base-cased-sst2)
    • datasets dataset glue, subset sst2, split validation
      • Correct/Whole: 785/872
      • Accuracy: 90.02%)
  • STS-b (distilbert-base-cased-stsb)
    • datasets dataset glue, subset stsb, split validation
    • Pearson correlation: 0.8421540899520146
    • Spearman correlation: 0.8407155030382939

distilbert-base-uncased

  • AG News (distilbert-base-uncased-ag-news)
    • datasets dataset ag_news, split test
      • Correct/Whole: 944/1000
      • Accuracy: 94.40%
  • CoLA (distilbert-base-uncased-cola)
    • datasets dataset glue, subset cola, split validation
      • Correct/Whole: 786/1000
      • Accuracy: 78.60%
  • IMDB (distilbert-base-uncased-imdb)
    • datasets dataset imdb, split test
      • Correct/Whole: 903/1000
      • Accuracy: 90.30%
  • MNLI matched (distilbert-base-uncased-mnli)
    • datasets dataset glue, subset mnli, split validation_matched
      • Correct/Whole: 817/1000
      • Accuracy: 81.70%
  • MRPC (distilbert-base-uncased-mrpc)
    • datasets dataset glue, subset mrpc, split validation
      • Correct/Whole: 350/408
      • Accuracy: 85.78%
  • QNLI (distilbert-base-uncased-qnli)
    • datasets dataset glue, subset qnli, split validation
      • Correct/Whole: 860/1000
      • Accuracy: 86.00%
  • Recognizing Textual Entailment (distilbert-base-uncased-rte)
    • datasets dataset glue, subset rte, split validation
      • Correct/Whole: 180/277
      • Accuracy: 64.98%
  • STS-b (distilbert-base-uncased-stsb)
    • datasets dataset glue, subset stsb, split validation
    • Pearson correlation: 0.8421540899520146
    • Spearman correlation: 0.8407155030382939
  • WNLI (distilbert-base-uncased-wnli)
    • datasets dataset glue, subset wnli, split validation
      • Correct/Whole: 40/71
      • Accuracy: 56.34%

roberta-base

  • AG News (roberta-base-ag-news)
    • datasets dataset ag_news, split test
      • Correct/Whole: 947/1000
      • Accuracy: 94.70%
  • CoLA (roberta-base-cola)
    • datasets dataset glue, subset cola, split validation
      • Correct/Whole: 857/1000
      • Accuracy: 85.70%
  • IMDB (roberta-base-imdb)
    • datasets dataset imdb, split test
      • Correct/Whole: 941/1000
      • Accuracy: 94.10%
  • Movie Reviews [Rotten Tomatoes] (roberta-base-mr)
    • datasets dataset rotten_tomatoes, split validation
      • Correct/Whole: 899/1000
      • Accuracy: 89.90%
    • datasets dataset rotten_tomatoes, split test
      • Correct/Whole: 883/1000
      • Accuracy: 88.30%
  • MRPC (roberta-base-mrpc)
    • datasets dataset glue, subset mrpc, split validation
      • Correct/Whole: 371/408
      • Accuracy: 91.18%
  • QNLI (roberta-base-qnli)
    • datasets dataset glue, subset qnli, split validation
      • Correct/Whole: 917/1000
      • Accuracy: 91.70%
  • Recognizing Textual Entailment (roberta-base-rte)
    • datasets dataset glue, subset rte, split validation
      • Correct/Whole: 217/277
      • Accuracy: 78.34%
  • SST-2 (roberta-base-sst2)
    • datasets dataset glue, subset sst2, split validation
      • Correct/Whole: 820/872
      • Accuracy: 94.04%)
  • STS-b (roberta-base-stsb)
    • datasets dataset glue, subset stsb, split validation
    • Pearson correlation: 0.906067852162708
    • Spearman correlation: 0.9025045272903051
  • WNLI (roberta-base-wnli)
    • datasets dataset glue, subset wnli, split validation
      • Correct/Whole: 40/71
      • Accuracy: 56.34%

xlnet-base-cased

  • CoLA (xlnet-base-cased-cola)
    • datasets dataset glue, subset cola, split validation
      • Correct/Whole: 800/1000
      • Accuracy: 80.00%
  • IMDB (xlnet-base-cased-imdb)
    • datasets dataset imdb, split test
      • Correct/Whole: 957/1000
      • Accuracy: 95.70%
  • Movie Reviews [Rotten Tomatoes] (xlnet-base-cased-mr)
    • datasets dataset rotten_tomatoes, split validation
      • Correct/Whole: 908/1000
      • Accuracy: 90.80%
    • datasets dataset rotten_tomatoes, split test
      • Correct/Whole: 876/1000
      • Accuracy: 87.60%
  • MRPC (xlnet-base-cased-mrpc)
    • datasets dataset glue, subset mrpc, split validation
      • Correct/Whole: 363/408
      • Accuracy: 88.97%
  • Recognizing Textual Entailment (xlnet-base-cased-rte)
    • datasets dataset glue, subset rte, split validation
      • Correct/Whole: 196/277
      • Accuracy: 70.76%
  • STS-b (xlnet-base-cased-stsb)
    • datasets dataset glue, subset stsb, split validation
    • Pearson correlation: 0.883111673280641
    • Spearman correlation: 0.8773439961182335
  • WNLI (xlnet-base-cased-wnli)
    • datasets dataset glue, subset wnli, split validation
      • Correct/Whole: 41/71
      • Accuracy: 57.75%

More details on TextAttack models (details on NLP task, output type, SOTA on paperswithcode; model card on huggingface):

Fine-tuned Model NLP Task Input type Output Type paperswithcode.com SOTA huggingface.co Model Card
albert-base-v2-CoLA linguistic acceptability single sentences binary (1=acceptable/ 0=unacceptable) https://paperswithcode.com/sota/linguistic-acceptability-on-cola https://huggingface.co/textattack/albert-base-v2-CoLA
bert-base-uncased-CoLA linguistic acceptability single sentences binary (1=acceptable/ 0=unacceptable) none yet https://huggingface.co/textattack/bert-base-uncased-CoLA
distilbert-base-cased-CoLA linguistic acceptability single sentences binary (1=acceptable/ 0=unacceptable) https://paperswithcode.com/sota/linguistic-acceptability-on-cola https://huggingface.co/textattack/distilbert-base-cased-CoLA
distilbert-base-uncased-CoLA linguistic acceptability single sentences binary (1=acceptable/ 0=unacceptable) https://paperswithcode.com/sota/linguistic-acceptability-on-cola https://huggingface.co/textattack/distilbert-base-uncased-CoLA
roberta-base-CoLA linguistic acceptability single sentences binary (1=acceptable/ 0=unacceptable) https://paperswithcode.com/sota/linguistic-acceptability-on-cola https://huggingface.co/textattack/roberta-base-CoLA
xlnet-base-cased-CoLA linguistic acceptability single sentences binary (1=acceptable/ 0=unacceptable) https://paperswithcode.com/sota/linguistic-acceptability-on-cola https://huggingface.co/textattack/xlnet-base-cased-CoLA
albert-base-v2-RTE natural language inference sentence pairs (1 premise and 1 hypothesis) binary(0=entailed/1=not entailed) https://paperswithcode.com/sota/natural-language-inference-on-rte https://huggingface.co/textattack/albert-base-v2-RTE
albert-base-v2-snli natural language inference sentence pairs accuracy (0=entailment, 1=neutral,2=contradiction) none yet https://huggingface.co/textattack/albert-base-v2-snli
albert-base-v2-WNLI natural language inference sentence pairs binary https://paperswithcode.com/sota/natural-language-inference-on-wnli https://huggingface.co/textattack/albert-base-v2-WNLI
bert-base-uncased-MNLI natural language inference sentence pairs (1 premise and 1 hypothesis) accuracy (0=entailment, 1=neutral,2=contradiction) none yet https://huggingface.co/textattack/bert-base-uncased-MNLI
bert-base-uncased-QNLI natural language inference question/answer pairs binary (1=unanswerable/ 0=answerable) none yet https://huggingface.co/textattack/bert-base-uncased-QNLI
bert-base-uncased-RTE natural language inference sentence pairs (1 premise and 1 hypothesis) binary(0=entailed/1=not entailed) none yet https://huggingface.co/textattack/bert-base-uncased-RTE
bert-base-uncased-snli natural language inference sentence pairs accuracy (0=entailment, 1=neutral,2=contradiction) none yet https://huggingface.co/textattack/bert-base-uncased-snli
bert-base-uncased-WNLI natural language inference sentence pairs binary none yet https://huggingface.co/textattack/bert-base-uncased-WNLI
distilbert-base-cased-snli natural language inference sentence pairs accuracy (0=entailment, 1=neutral,2=contradiction) none yet https://huggingface.co/textattack/distilbert-base-cased-snli
distilbert-base-uncased-MNLI natural language inference sentence pairs (1 premise and 1 hypothesis) accuracy (0=entailment,1=neutral, 2=contradiction) none yet https://huggingface.co/textattack/distilbert-base-uncased-MNLI
distilbert-base-uncased-RTE natural language inference sentence pairs (1 premise and 1 hypothesis) binary(0=entailed/1=not entailed) https://paperswithcode.com/sota/natural-language-inference-on-rte https://huggingface.co/textattack/distilbert-base-uncased-RTE
distilbert-base-uncased-WNLI natural language inference sentence pairs binary https://paperswithcode.com/sota/natural-language-inference-on-wnli https://huggingface.co/textattack/distilbert-base-uncased-WNLI
roberta-base-QNLI natural language inference question/answer pairs binary (1=unanswerable/ 0=answerable) https://paperswithcode.com/sota/natural-language-inference-on-qnli https://huggingface.co/textattack/roberta-base-QNLI
roberta-base-RTE natural language inference sentence pairs (1 premise and 1 hypothesis) binary(0=entailed/1=not entailed) https://paperswithcode.com/sota/natural-language-inference-on-rte https://huggingface.co/textattack/roberta-base-RTE
roberta-base-WNLI natural language inference sentence pairs binary https://paperswithcode.com/sota/natural-language-inference-on-wnli https://huggingface.co/textattack/roberta-base-WNLI
xlnet-base-cased-RTE natural language inference sentence pairs (1 premise and 1 hypothesis) binary(0=entailed/1=not entailed) https://paperswithcode.com/sota/ natural-language-inference-on-rte https://huggingface.co/textattack/xlnet-base-cased-RTE
xlnet-base-cased-WNLI natural language inference sentence pairs binary none yet https://huggingface.co/textattack/xlnet-base-cased-WNLI
albert-base-v2-QQP paraphase similarity question pairs binary (1=similar/0=not similar) https://paperswithcode.com/sota/question-answering-on-quora-question-pairs https://huggingface.co/textattack/albert-base-v2-QQP
bert-base-uncased-QQP paraphase similarity question pairs binary (1=similar/0=not similar) https://paperswithcode.com/sota/question-answering-on-quora-question-pairs https://huggingface.co/textattack/bert-base-uncased-QQP
distilbert-base-uncased-QNLI question answering/natural language inference question/answer pairs binary (1=unanswerable/ 0=answerable) https://paperswithcode.com/sota/natural-language-inference-on-qnli https://huggingface.co/textattack/distilbert-base-uncased-QNLI
distilbert-base-cased-QQP question answering/paraphase similarity question pairs binary (1=similar/ 0=not similar) https://paperswithcode.com/sota/question-answering-on-quora-question-pairs https://huggingface.co/textattack/distilbert-base-cased-QQP
albert-base-v2-STS-B semantic textual similarity sentence pairs similarity (0.0 to 5.0) https://paperswithcode.com/sota/semantic-textual-similarity-on-sts-benchmark https://huggingface.co/textattack/albert-base-v2-STS-B
bert-base-uncased-MRPC semantic textual similarity sentence pairs binary (1=similar/0=not similar) none yet https://huggingface.co/textattack/bert-base-uncased-MRPC
bert-base-uncased-STS-B semantic textual similarity sentence pairs similarity (0.0 to 5.0) none yet https://huggingface.co/textattack/bert-base-uncased-STS-B
distilbert-base-cased-MRPC semantic textual similarity sentence pairs binary (1=similar/0=not similar) https://paperswithcode.com/sota/semantic-textual-similarity-on-mrpc https://huggingface.co/textattack/distilbert-base-cased-MRPC
distilbert-base-cased-STS-B semantic textual similarity sentence pairs similarity (0.0 to 5.0) https://paperswithcode.com/sota/semantic-textual-similarity-on-sts-benchmark https://huggingface.co/textattack/distilbert-base-cased-STS-B
distilbert-base-uncased-MRPC semantic textual similarity sentence pairs binary (1=similar/0=not similar) https://paperswithcode.com/sota/semantic-textual-similarity-on-mrpc https://huggingface.co/textattack/distilbert-base-uncased-MRPC
roberta-base-MRPC semantic textual similarity sentence pairs binary (1=similar/0=not similar) https://paperswithcode.com/sota/semantic-textual-similarity-on-mrpc https://huggingface.co/textattack/roberta-base-MRPC
roberta-base-STS-B semantic textual similarity sentence pairs similarity (0.0 to 5.0) https://paperswithcode.com/sota/semantic-textual-similarity-on-sts-benchmark https://huggingface.co/textattack/roberta-base-STS-B
xlnet-base-cased-MRPC semantic textual similarity sentence pairs binary (1=similar/0=not similar) https://paperswithcode.com/sota/semantic-textual-similarity-on-mrpc https://huggingface.co/textattack/xlnet-base-cased-MRPC
xlnet-base-cased-STS-B semantic textual similarity sentence pairs similarity (0.0 to 5.0) https://paperswithcode.com/sota/semantic-textual-similarity-on-sts-benchmark https://huggingface.co/textattack/xlnet-base-cased-STS-B
albert-base-v2-imdb sentiment analysis movie reviews binary (1=good/0=bad) none yet https://huggingface.co/textattack/albert-base-v2-imdb
albert-base-v2-rotten-tomatoes sentiment analysis movie reviews binary (1=good/0=bad) none yet https://huggingface.co/textattack/albert-base-v2-rotten-tomatoes
albert-base-v2-SST-2 sentiment analysis phrases accuracy (0.0000 to 1.0000) https://paperswithcode.com/sota/sentiment-analysis-on-sst-2-binary https://huggingface.co/textattack/albert-base-v2-SST-2
albert-base-v2-yelp-polarity sentiment analysis yelp reviews binary (1=good/0=bad) none yet https://huggingface.co/textattack/albert-base-v2-yelp-polarity
bert-base-uncased-imdb sentiment analysis movie reviews binary (1=good/0=bad) none yet https://huggingface.co/textattack/bert-base-uncased-imdb
bert-base-uncased-rotten-tomatoes sentiment analysis movie reviews binary (1=good/0=bad) none yet https://huggingface.co/textattack/bert-base-uncased-rotten-tomatoes
bert-base-uncased-SST-2 sentiment analysis phrases accuracy (0.0000 to 1.0000) https://paperswithcode.com/sota/sentiment-analysis-on-sst-2-binary https://huggingface.co/textattack/bert-base-uncased-SST-2
bert-base-uncased-yelp-polarity sentiment analysis yelp reviews binary (1=good/0=bad) https://paperswithcode.com/sota/sentiment-analysis-on-yelp-binary https://huggingface.co/textattack/bert-base-uncased-yelp-polarity
cnn-imdb sentiment analysis movie reviews binary (1=good/0=bad) https://paperswithcode.com/sota/sentiment-analysis-on-imdb none
cnn-mr sentiment analysis movie reviews binary (1=good/0=bad) none yet none
cnn-sst2 sentiment analysis phrases accuracy (0.0000 to 1.0000) https://paperswithcode.com/sota/sentiment-analysis-on-sst-2-binary none
cnn-yelp sentiment analysis yelp reviews binary (1=good/0=bad) https://paperswithcode.com/sota/sentiment-analysis-on-yelp-binary none
distilbert-base-cased-SST-2 sentiment analysis phrases accuracy (0.0000 to 1.0000) https://paperswithcode.com/sota/sentiment-analysis-on-sst-2-binary https://huggingface.co/textattack/distilbert-base-cased-SST-2
distilbert-base-uncased-imdb sentiment analysis movie reviews binary (1=good/0=bad) https://paperswithcode.com/sota/sentiment-analysis-on-imdb https://huggingface.co/textattack/distilbert-base-uncased-imdb
distilbert-base-uncased-rotten-tomatoes sentiment analysis movie reviews binary (1=good/0=bad) none yet https://huggingface.co/textattack/distilbert-base-uncased-rotten-tomatoes
lstm-imdb sentiment analysis movie reviews binary (1=good/0=bad) https://paperswithcode.com/sota/sentiment-analysis-on-imdb none
lstm-mr sentiment analysis movie reviews binary (1=good/0=bad) none yet none
lstm-sst2 sentiment analysis phrases accuracy (0.0000 to 1.0000) none yet none
lstm-yelp sentiment analysis yelp reviews binary (1=good/0=bad) none yet none
roberta-base-imdb sentiment analysis movie reviews binary (1=good/0=bad) none yet https://huggingface.co/textattack/roberta-base-imdb
roberta-base-rotten-tomatoes sentiment analysis movie reviews binary (1=good/0=bad) none yet https://huggingface.co/textattack/roberta-base-rotten-tomatoes
roberta-base-SST-2 sentiment analysis phrases accuracy (0.0000 to 1.0000) https://paperswithcode.com/sota/sentiment-analysis-on-sst-2-binary https://huggingface.co/textattack/roberta-base-SST-2
xlnet-base-cased-imdb sentiment analysis movie reviews binary (1=good/0=bad) none yet https://huggingface.co/textattack/xlnet-base-cased-imdb
xlnet-base-cased-rotten-tomatoes sentiment analysis movie reviews binary (1=good/0=bad) none yet https://huggingface.co/textattack/xlnet-base-cased-rotten-tomatoes
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