Using LIME to explain the predictions from a BERT model, it looks like "the", "and", "or" are "very important" features, and thus I don't think the model is learning anything interesting. Any tips?

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  • transformers-interpret

    Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

  • You could look at the Transformers Interpret python library: https://github.com/cdpierse/transformers-interpret

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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