time-saving_stated_aim_classifier

Name: time-saving_stated_aim_classifier
Author: matthewleechen

—

matthewleechen

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Quick Summary

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 time-saving objective.

Code Examples

text

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 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

text

{'eval_loss': 0.5350350737571716,
 'eval_accuracy': 0.89,
 'eval_precision': 0.8972633319553535,
 'eval_recall': 0.89,
 'eval_f1': 0.8891426257718393,
 'eval_runtime': 0.4081,
 'eval_samples_per_second': 245.053,
 'eval_steps_per_second': 2.451}

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