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medmcqa-mobile-bert-uncased

This model is a fine-tuned version of google/mobilebert-uncased on a MedMCQA dataset. It achieves the following results on the evaluation set:

  • Train Loss: 4.0974
  • Validation Loss: 1.5722
  • Train Accuracy: 0.244
  • Epoch: 9

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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 5000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Accuracy Epoch
4852.5933 15.4345 0.245 0
168.1700 10.9270 0.27 1
103.5470 29.7673 0.243 2
95.7810 15.3191 0.268 3
62.5387 5.4845 0.262 4
43.1666 9.3354 0.239 5
32.7722 27.9195 0.24 6
25.1578 5.1954 0.228 7
12.7365 2.1180 0.219 8
4.0974 1.5722 0.244 9

Framework versions

  • Transformers 4.37.2
  • TensorFlow 2.15.0
  • Datasets 2.17.1
  • Tokenizers 0.15.2
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