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