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Fine-tuned roberta-base for detecting paragraphs on the topic of 'Information Sources and Research'

Description

This is a fine tuned roberta-base model for detecting whether paragraphs drawn from ethnographic source material are about 'Information Sources and Research'.

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_information-sources")
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 93.1
Recall 93.2
F1 93.1
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Safetensors
Model size
125M params
Tensor type
F32
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