# BERTSentiment **`class BERTSentiment(config)`** Bases: [`Classifier`](squirro.lib.nlp.steps.classifiers.Classifier.md#squirro.lib.nlp.steps.classifiers.Classifier) The BERT Sentiment [`Classifier`](squirro.lib.nlp.steps.classifiers.Classifier.md#squirro.lib.nlp.steps.classifiers.Classifier) detects the sentiments of a text fragment using transformer bases pre-trained models. **Note** - **We provide the following pre-trained models:** - [DistilBERT](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english): The model predicts the sentiment [“positive”, “negative”] of the input text. - [FinBERT](https://huggingface.co/ProsusAI/finbert): It is a BERT language model finetuned on a financial corpus. The model predicts the sentiment [“positive”, “neutral”, “negative”] of the input text. FinBERT is not installed by default, please install it using ´sudo yum install squirro-finbert´. - Truncation is activated for the execution of model. It shortens the textual input if it exceeds the maximum acceptable input length. **Input** - the input field needs to be of type [`str`](https://docs.python.org/3.11/library/stdtypes.html#str). **Output** - the output field is filled with data of type [`list`](https://docs.python.org/3.11/library/stdtypes.html#list) [ [`str`](https://docs.python.org/3.11/library/stdtypes.html#str) ]. The list contains only one element. Parameters - `type` ([`str`](https://docs.python.org/3.11/library/stdtypes.html#str)) – bertsentiment - `model_name` ([`str`](https://docs.python.org/3.11/library/stdtypes.html#str)) – finbert or distilbert - `pretrained_models_dir` ([`str`](https://docs.python.org/3.11/library/stdtypes.html#str)`, ``None`) – Directory where the pre-trained models are stored (default: “/var/lib/squirro/machinelearning/pretrained_models”) **Example** ```json { "step": "classifier", "type": "bertsentiment", "model_name":"distilbert", "input_fields": ["normalized_extract"], "output_field": "prediction", "label_field": "" } ``` Methods SummaryMethods Documentation **`process_doc(doc)`** Process a document Parameters `doc` ([`Document`](../technical/libnlp/base.md#squirro.lib.nlp.document.Document)) – Document Returns Processed document Return type [Document](../technical/libnlp/base.md#squirro.lib.nlp.document.Document)