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--- |
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language: |
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- en |
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license: apache-2.0 |
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library_name: transformers |
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pipeline_tag: text-classification |
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tags: |
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- motivational-interviewing |
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metrics: |
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- f1 |
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widget: |
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- text: >- |
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I'm planning on having tuna, ground tuna, chopped celery, and chopped black |
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pepper, and half a apple. |
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example_title: change_talk_goal_talk_and_opportunities |
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--- |
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# Model Card for roberta-base-motivational-interviewing |
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⚠ WARNING: This is a preliminary model that is still actively under development. ⚠ |
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This is a [roBERTa-base](https://huggingface.co/roberta-base) model fine-tuned on a small dataset of conversations between health coaches and cancer survivors. |
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# How to Get Started with the Model |
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You can use this model directly with a pipeline for text classification: |
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```python |
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>>> import transformers |
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>>> model_name = "clulab/roberta-base-motivational-interviewing" |
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>>> classifier = transformers.TextClassificationPipeline( |
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... tokenizer=transformers.AutoTokenizer.from_pretrained(model_name), |
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... model=transformers.AutoModelForSequenceClassification.from_pretrained(model_name)) |
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>>> classifier("I'm planning on having tuna, ground tuna, chopped celery, and chopped black pepper, and half a apple.") |
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[{'label': 'change_talk_goal_talk_and_opportunities', 'score': 0.9995419979095459}] |
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``` |
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# Model Details |
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- **Developed by:** [Steven Bethard](https://bethard.github.io/) |
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- **Parent Model:** [roBERTa-base](https://huggingface.co/roberta-base) |
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- **GitHub Repo:** [LIvES repo](https://github.com/clulab/lives) |
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# Uses |
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The model is intended to be used for text classification, taking as input conversational utterances and predicting as output different categories of motivational interviewing behaviors. |
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It is intended for use by health coaches to assist when reviewing their past calls with participants. Its predictions should not be used without manual review. |
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# Training Details |
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The model was trained on data annotated under the grant [Using Natural Language Processing to Determine Predictors of Healthy Diet and Physical Activity Behavior Change in Ovarian Cancer Survivors (NIH NCI R21CA256680)](https://reporter.nih.gov/project-details/10510666). A [roberta-base](https://huggingface.co/roberta-base) model was fine-tuned on that dataset, with texts tokenized using the standard [roberta-base](https://huggingface.co/roberta-base) tokenizer. |
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# Evaluation |
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On the test partition of the R21CA256680 dataset, the model achieves 0.60 precision and 0.46 recall. |
