Labor Augmenting Stated Aim Classifier

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-augmenting objective.

Labels were manually generated and then checked with Gemini 2.0 Flash with the attached prompt.

Hyperparameters: lr = 7e-5 batch size = 128

Test set results:

{'eval_loss': 0.2932845950126648,
 'eval_accuracy': 0.9,
 'eval_precision': 0.9,
 'eval_recall': 0.9,
 'eval_f1': 0.9,
 'eval_runtime': 0.3819,
 'eval_samples_per_second': 157.109,
 'eval_steps_per_second': 2.618}