ONNX convert DistilBERT base uncased finetuned SST 2 Conversion of distilbert base uncased finetuned sst 2 english This model is a fine tune checkpoint of DistilBERT base uncased, fine tuned on SST 2. This model reaches an accuracy of 91.3 on the dev set (for comparison, Bert bert base uncased version reaches an accuracy of 92.7). For more details about DistilBERT, we encourage users to check out this model card. Fine tuning hyper parameters learning rate = 1e 5 batch size = 32 warmup = 600 max seq length = 128 num train epochs = 3.0 Bias Based on a few experimentations, we observed that this model could produce biased predictions that target underrepresented populations. For instance, for sentences like This film was filmed in COUNTRY , this binary classification model will give radically different probabilities for the positive label depending on the country (0.89 if the country is France, but 0.08 if the country is Afghanistan) when nothing in the input indicates such a strong semantic shift. In this colab, Aurélien Géron made an interesting map plotting these probabilities for each country. We strongly advise users to thoroughly probe these aspects on their use cases in order…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy