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
5.2930	0.0113	2.0658	3.9415	0.0117	0.9401	0
4.6215	0.0121	0.8917	3.7803	0.0120	0.9294	1
4.4086	0.0128	0.8403	3.6070	0.0124	0.9223	2
4.1842	0.0135	0.8337	3.4291	0.0128	0.8867	3
3.9981	0.0141	0.8182	3.3251	0.0131	0.8750	4
3.8531	0.0145	0.8058	3.2385	0.0133	0.8699	5
3.7345	0.0149	0.7925	3.1751	0.0134	0.8665	6
3.6307	0.0152	0.7851	3.1031	0.0136	0.8507	7
3.5437	0.0155	0.7717	3.0752	0.0138	0.8286	8
3.4649	0.0157	0.7651	3.0334	0.0139	0.8417	9
3.3926	0.0159	0.7531	3.0022	0.0139	0.8413	10
3.3262	0.0162	0.7462	2.9669	0.0140	0.8264	11
3.2625	0.0164	0.7367	2.9342	0.0141	0.8520	12
3.1979	0.0166	0.7231	2.9046	0.0144	0.8196	13
3.1319	0.0169	0.7133	2.8607	0.0145	0.8026	14
3.0616	0.0172	0.7007	2.8165	0.0146	0.7788	15
2.9792	0.0176	0.6816	2.7552	0.0149	0.7643	16
2.8905	0.0180	0.6641	2.6788	0.0151	0.7473	17
2.7749	0.0186	0.6424	2.5824	0.0155	0.7241	18
2.6263	0.0193	0.6159	2.4206	0.0161	0.7047	19
2.4352	0.0203	0.5829	2.2230	0.0168	0.6500	20
2.1941	0.0216	0.5411	2.0349	0.0175	0.5980	21
1.9184	0.0231	0.4922	1.7850	0.0184	0.5659	22
1.6174	0.0249	0.4371	1.5664	0.0192	0.5081	23
1.3542	0.0265	0.3851	1.3992	0.0199	0.4690	24
1.1499	0.0278	0.3408	1.2512	0.0205	0.4299	25
0.9878	0.0288	0.3029	1.1479	0.0209	0.4013	26
0.8600	0.0297	0.2735	1.0527	0.0213	0.3755	27
0.7516	0.0305	0.2441	0.9803	0.0216	0.3570	28
0.6626	0.0311	0.2197	0.9314	0.0219	0.3416	29

bigmorning/whisper_syl_cv12_pad_lob100_low__0030

whisper_syl_cv12_pad_lob100_low__0030