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[R] Low accuracy on small English dataset using XLNet

I compared accuracies on small dataset, got 2 classes, which are negative and positive, each class has 5k of sentences. You can check it here english-polarity. All notebooks finetune on single Tesla V100, 100 max length of sentences. 80% to train, 20% to test. All notebooks do early stopping with 3 patients, and I will pick highest test accuracy as the benchmark.

  1. BERT English Base, test accuracy 81%.
  2. GPT2 345M, test accuracy 79%.
  3. XLnet Large, test accuracy 51%.

I am not sure what is wrong here maybe not follow an exact batch size and max length?, I doubled check all the code to transform into notebooks based, everything looks same, just a bit tweak to make it notebook-able. Great model and repository, https://github.com/zihangdai/xlnet!

submitted by /u/huseinzol05
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.