DistilBERT base uncased finetuned SST 2 Table of Contents Model Details How to Get Started With the Model Uses Risks, Limitations and Biases Training Model Details Model Description: 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). Developed by: Hugging Face Model Type: Text Classification Language(s): English License: Apache 2.0 Parent Model: For more details about DistilBERT, we encourage users to check out this model card. Resources for more information: Model Documentation DistilBERT paper How to Get Started With the Model Example of single label classification: Uses Direct Use This model can be used for topic classification. You can use the raw model for either masked language modeling or next sentence prediction, but it's mostly intended to be fine tuned on a downstream task. See the model hub to look for fine tuned versions on a task that interests you. Misuse and Out of scope Use The model should not be used to intentionally create hostile or alienating environments for people. In addition, the model was…
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