ninaa510/distilbert-finetuned-medical-diagnosis

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distilbert-finetuned-medical-diagnosis

This model is a fine-tuned version of distilbert/distilbert-base-cased on the dataset here.

It achieves an accuracy of 58.68% on the test set of the dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —optimizer: {'name': 'Adam', 'weightdecay': None, 'clipnorm': None, 'globalclipnorm': 1.0, 'clipvalue': None, 'useema': False, 'emamomentum': 0.99, 'emaoverwritefrequency': None, 'jitcompile': True, 'islegacyoptimizer': False, 'learningrate': {'module': 'keras.optimizers.schedules', 'classname': 'PolynomialDecay', 'config': {'initiallearningrate': 5e-05, 'decaysteps': 1663, 'endlearningrate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registeredname': None}, 'beta1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• —training_precision: float32

Training results

Framework versions

• —Transformers 4.41.0
• —TensorFlow 2.15.0
• —Datasets 2.19.1
• —Tokenizers 0.19.1