Fine-tuned roberta-base for detecting paragraphs on the topic of 'Education and Knowledge'
Description
This is a fine tuned roberta-base model for detecting whether paragraphs drawn from ethnographic source material are about 'Education and Knowledge'.
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_education")
classifier("Example text to classify")
Training data
...
Training procedure
...
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 | 94.0 |
Recall | 94.5 |
F1 | 94.2 |
- Downloads last month
- 4
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.