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gptmurdock/classifier-150
classifier-150 is a text classification model from gptmurdock. Use it when you need a label for a piece of text. It is set up for transformers.
This is a fine tuned roberta-base model for detecting whether paragraphs drawn from ethnographic source material classified under the main subject 'Life Cycle' is more specifically about '150'.
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From the Hugging Face model README
This is a fine tuned roberta-base model for detecting whether paragraphs drawn from ethnographic source material classified under the main subject 'Life Cycle' is more specifically about '150'.
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-150")
classifier("Example text to classify")
...
...
We use a 60-20-20 train-val-test split, and fine-tuned roberta-base for 5 epochs (lr = 2e-5, batch size = 40).
Evals on the test set are reported below.
| Metric | Value |
|---|---|
| Precision | 91.2 |
| Recall | 91.2 |
| F1 | 91.2 |