metadata
license: mit
datasets:
- tweet_eval
- bookcorpus
- wikipedia
- cc_news
language:
- en
metrics:
- accuracy
pipeline_tag: text-classification
tags:
- medical
Model Card for Model ID
Pretrained model on English language for text classification. Model trained from tweet_emotion_eval (roberta-base fine-tuned on emotion task of tweet_eval dataset) on psychotherapy text transcripts.
Given a sentence, this model provides a binary classification as either symptomatic or non-symptomatic where symptomatic means the sentence displays signs of anxiety and/or depression.
Model Details
Model Description
- Developed by: [More Information Needed]
- Funded by [optional]: Queen's University
- Model type: RoBERTa
- Language(s) (NLP): English
- License: MIT
- Finetuned from model: elonzano/tweet_emotion_eval
Uses
Direct Use
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How to Get Started with the Model
Use the code below to get started with the model.
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Training Details
Training Data
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Training Procedure
Preprocessing [optional]
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Training Hyperparameters
- Training regime: [More Information Needed]
Speeds, Sizes, Times [optional]
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Evaluation
Testing Data, Factors & Metrics
Testing Data
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Factors
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Metrics
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Results
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