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matthewleechen/labor-saving_stated_aim_classifier
labor-saving_stated_aim_classifier is a text classification model from matthewleechen. Use it when you need a label for a piece of text. It is set up for transformers.
This is a roberta-base model that is trained to classify whether a set of explicit stated aims extracted from a British historical patent includes a labor-saving objective.
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From the Hugging Face model README
This is a roberta-base model that is trained to classify whether a set of explicit stated aims extracted from a British historical patent includes a labor-saving objective.
Labels were manually generated and then checked with Gemini 2.0 Flash with the attached prompt.
Hyperparameters: lr = 6e-5 batch size = 128
Test set results:
{'eval_loss': 0.28036537766456604,
'eval_accuracy': 0.9,
'eval_precision': 0.9,
'eval_recall': 0.9,
'eval_f1': 0.9,
'eval_runtime': 0.4135,
'eval_samples_per_second': 241.832,
'eval_steps_per_second': 2.418}