optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: float32

Train Loss	Train Accuracy	Train Wermet	Validation Loss	Validation Accuracy	Validation Wermet	Epoch
0.0010	0.0795	8.7507	0.5575	0.0767	7.6778	0
0.0013	0.0795	8.9468	0.5652	0.0766	8.3360	1
0.0025	0.0795	8.7338	0.5673	0.0765	8.3770	2
0.0019	0.0795	8.9450	0.5623	0.0766	7.7117	3
0.0011	0.0795	8.9053	0.5609	0.0767	7.5155	4
0.0012	0.0795	8.8862	0.5667	0.0767	8.2913	5
0.0009	0.0795	8.7510	0.5642	0.0766	7.9083	6
0.0037	0.0795	9.3428	0.5717	0.0764	8.2631	7
0.0031	0.0795	9.2135	0.5636	0.0766	8.2384	8
0.0011	0.0795	8.9730	0.5605	0.0767	8.3958	9
0.0005	0.0795	9.3749	0.5552	0.0768	8.0800	10
0.0003	0.0795	9.3340	0.5584	0.0768	8.1322	11
0.0005	0.0795	9.2292	0.5687	0.0767	8.5576	12
0.0037	0.0795	9.2838	0.5751	0.0765	7.4189	13
0.0038	0.0795	8.7270	0.5605	0.0767	7.7098	14
0.0012	0.0795	8.8259	0.5563	0.0768	8.2647	15
0.0005	0.0795	9.0553	0.5620	0.0768	8.5020	16
0.0004	0.0795	9.1734	0.5607	0.0768	8.0252	17
0.0003	0.0795	9.0084	0.5571	0.0769	8.1563	18
0.0014	0.0795	8.7153	0.5804	0.0765	7.8654	19
0.0058	0.0794	8.8460	0.5706	0.0766	7.4342	20
0.0020	0.0795	8.6599	0.5612	0.0767	7.7369	21
0.0007	0.0795	8.6456	0.5543	0.0768	7.4625	22
0.0008	0.0795	8.3246	0.5620	0.0768	7.4475	23
0.0012	0.0795	7.9451	0.5615	0.0768	7.0907	24
0.0025	0.0795	8.1065	0.5619	0.0768	7.7020	25
0.0011	0.0795	8.4237	0.5710	0.0768	7.4035	26
0.0009	0.0795	8.3074	0.5641	0.0768	7.1747	27
0.0007	0.0795	8.5183	0.5688	0.0768	7.4310	28

bigmorning/whisper_charsplit_new_round2__0029

whisper_charsplit_new_round2__0029