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 Do Wer	Validation Loss	Validation Accuracy	Validation Do Wer	Epoch
9.9191	0.0046	1.0	8.5836	0.0067	1.0	0
8.0709	0.0083	1.0	7.4667	0.0089	1.0	1
7.1652	0.0100	1.0	6.8204	0.0112	1.0	2
6.7196	0.0114	1.0	6.5192	0.0114	1.0	3
6.4115	0.0115	1.0	6.2357	0.0115	1.0	4
6.1085	0.0115	1.0	5.9657	0.0115	1.0	5
5.8206	0.0115	1.0	5.7162	0.0115	1.0	6
5.5567	0.0115	1.0	5.4963	0.0115	1.0	7
5.3223	0.0116	1.0	5.3096	0.0116	1.0	8
5.1222	0.0117	1.0	5.1600	0.0117	1.0	9
4.9580	0.0117	1.0	5.0391	0.0118	1.0	10
4.8251	0.0119	1.0	4.9427	0.0118	1.0	11
4.7171	0.0119	1.0	4.8691	0.0119	1.0	12
4.6284	0.0121	1.0	4.8123	0.0120	1.0	13
4.5508	0.0121	1.0	4.7620	0.0121	1.0	14
4.4855	0.0123	1.0	4.7260	0.0121	1.0	15
4.4305	0.0124	1.0	4.7018	0.0123	1.0	16
4.3788	0.0125	1.0	4.6738	0.0123	1.0	17
4.3305	0.0127	1.0	4.6525	0.0124	1.0	18
4.2860	0.0128	1.0	4.6401	0.0125	1.0	19
4.2451	0.0130	1.0	4.6234	0.0126	1.0	20
4.1994	0.0132	1.0	4.6077	0.0128	1.0	21
4.1521	0.0133	1.0	4.6098	0.0129	1.0	22
4.1148	0.0134	1.0	4.5919	0.0129	1.0	23
4.0701	0.0135	1.0	4.6038	0.0128	1.0	24
4.0199	0.0137	1.0	4.5777	0.0130	1.0	25
3.9631	0.0138	1.0	4.5734	0.0131	1.0	26
3.9175	0.0140	1.0	4.5866	0.0129	1.0	27
3.8690	0.0142	1.0	4.5900	0.0129	1.0	28
3.8276	0.0143	1.0	4.5602	0.0131	1.0	29
3.7499	0.0145	1.0	4.5619	0.0132	1.0	30
3.6968	0.0147	1.0	4.6203	0.0133	1.0	31
3.6714	0.0149	1.0	4.7075	0.0133	1.0	32
3.6318	0.0149	1.0	4.6638	0.0125	1.0	33
3.5897	0.0150	1.0	4.5822	0.0130	1.0	34

bigmorning/whisper_havest_0035

whisper_havest_0035