pliers.extractors.BertSentimentExtractor

class pliers.extractors.BertSentimentExtractor(pretrained_model='distilbert-base-uncased-finetuned-sst-2-english', tokenizer='bert-base-uncased', framework='pt', return_softmax=True, return_input=False, model_kwargs=None, tokenizer_kwargs=None)

Bases: BertExtractor

Extracts sentiment for sequences using BERT (or similar, e.g.

DistilBERT) models fine-tuned for sentiment classification.

Parameters

• pretrained_model (str) – A string specifying which transformer model to use (must be one fine-tuned for sentiment classification)

• tokenizer (str) – Type of tokenization used in the tokenization step.

• framework (str) – name deep learning framework to use. Must be ‘pt’ (PyTorch) or ‘tf’ (tensorflow). Defaults to ‘pt’.

• return_softmax (bool) – If True, the extractor returns softmaxed sentiment scores instead of raw model predictions.

• return_input (bool) – If True, the extractor returns an additional feature column with the encoded sequence.

• model_kwargs (dict) – Named arguments for pretrained model.

• tokenizer_kwargs (dict) – Named arguments for tokenizer.

__init__(pretrained_model='distilbert-base-uncased-finetuned-sst-2-english', tokenizer='bert-base-uncased', framework='pt', return_softmax=True, return_input=False, model_kwargs=None, tokenizer_kwargs=None)

transform(stim, *args, **kwargs)

Executes the transformation on the passed stim(s).

Parameters

• stims (str, Stim, list) –

  One or more stimuli to process. Must be one of:

  • A string giving the path to a file that can be read in as a Stim (e.g., a .txt file, .jpg image, etc.)

  • A Stim instance of any type.

  • An iterable of stims, where each element is either a string or a Stim.

• validation (str) –

  String specifying how validation errors should be handled. Must be one of:

  • ’strict’: Raise an exception on any validation error

  • ’warn’: Issue a warning for all validation errors

  • ’loose’: Silently ignore all validation errors

• args – Optional positional arguments to pass onto the internal _transform call.

• kwargs – Optional positional arguments to pass onto the internal _transform call.