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As discussed, this seems to either be a bug in the training code, or a consequence of poorly-chosen training data. For the training tests to be useful, they have to be sensitive to breaking the training algorithm.
The text was updated successfully, but these errors were encountered:
See #129 for the changes. The training looks fine for the toy example; however, we still have an issue with testing real datasets. Perhaps the issue comes from the datasets used. I will try to understand this.
As discussed, this seems to either be a bug in the training code, or a consequence of poorly-chosen training data. For the training tests to be useful, they have to be sensitive to breaking the training algorithm.
The text was updated successfully, but these errors were encountered: