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': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 280, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: float32

Train Loss	Validation Loss	Train Accuracy	Epoch
3.4316	3.2876	0.2078	0
3.0452	3.0083	0.2338	1
2.6954	2.7106	0.3766	2
2.3815	2.4910	0.4935	3
2.0499	2.3035	0.5584	4
1.8322	2.1419	0.5844	5
1.6292	1.9997	0.6104	6
1.4675	1.8933	0.6234	7
1.3115	1.8016	0.5974	8
1.2088	1.7273	0.6364	9
1.1053	1.6728	0.6623	10
1.0254	1.6284	0.6364	11
0.9600	1.6252	0.6494	12
0.9058	1.5662	0.6623	13
0.8675	1.5423	0.6623	14
0.8434	1.5208	0.6753	15
0.8356	1.5140	0.6753	16
0.8070	1.5024	0.6753	17
0.7749	1.4941	0.6753	18
0.7805	1.4913	0.6753	19
0.7764	1.4913	0.6753	20
0.7630	1.4913	0.6753	21
0.7806	1.4913	0.6753	22
0.7665	1.4913	0.6753	23
0.7803	1.4913	0.6753	24
0.7778	1.4913	0.6753	25
0.7781	1.4913	0.6753	26
0.7798	1.4913	0.6753	27
0.7845	1.4913	0.6753	28
0.7596	1.4913	0.6753	29