Fine-tuned roberta-base for detecting paragraphs on the topic of 'Basic Information'
Description
This is a fine tuned roberta-base model for detecting whether paragraphs drawn from ethnographic source material are about 'Basic Information'.
Usage
The easiest way to use this model at inference time is with the HF pipelines API.
from transformers import pipeline
classifier = pipeline("text-classification", model="gptmurdock/classifier-main_subjects_basic-information")
classifier("Example text to classify")
Training data
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Training procedure
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We use a 60-20-20 train-val-test split, and fine-tuned roberta-base for 5 epochs (lr = 2e-5, batch size = 40).
Evaluation
Evals on the test set are reported below.
| Metric | Value |
|---|---|
| Precision | 92.7 |
| Recall | 93.1 |
| F1 | 92.8 |
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