Text PredictionΒΆ
For supervised learning with text data, AutoGluon provides a simple fit() function that automatically produces high quality text prediction models (Transformer neural networks). Each training example may be a sentence, a short paragraph, comprised of multiple text fields (e.g. predicting how similar two sentences are), or may even contain additional numeric/categorical features beyond just text. The target values (labels) to predict may be continuous values (regression) or discrete categories (classification). A single call to predictor.fit() will train highly accurate neural networks on your provided text dataset, automatically leveraging accuracy-boosting techniques such as fine-tuning a pretrained NLP model (transfer learning) and hyperparameter optimization.
How to train high-quality text prediction models in under 5 minutes.
How TextPredictor can be applied to multimodal data tables with a mix of text, numeric, and categorical columns.
How to specify custom hyperparameters of the TextPredictor.
Build models on datasets with languages other than English.
How to use AutoMM to train models on single modal and multimodal data.