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
5.2961	0.0113	1.9043	3.9402	0.0116	0.9526	0
4.6207	0.0121	0.8740	3.7957	0.0120	0.9397	1
4.4142	0.0128	0.8473	3.6045	0.0124	0.8988	2
4.1915	0.0135	0.8361	3.4445	0.0128	0.9019	3
4.0072	0.0140	0.8260	3.3268	0.0131	0.8816	4
3.8559	0.0145	0.8084	3.2440	0.0133	0.8592	5
3.7359	0.0149	0.7986	3.1751	0.0135	0.8598	6
3.6368	0.0152	0.7891	3.1298	0.0136	0.8398	7
3.5465	0.0154	0.7775	3.0736	0.0138	0.8606	8
3.4710	0.0157	0.7681	3.0318	0.0138	0.8455	9
3.3988	0.0159	0.7603	3.0159	0.0139	0.8770	10
3.3279	0.0162	0.7504	2.9672	0.0141	0.8241	11
3.2611	0.0164	0.7397	2.9541	0.0141	0.8676	12
3.1996	0.0167	0.7284	2.8913	0.0144	0.7990	13
3.1311	0.0169	0.7162	2.8671	0.0145	0.7934	14
3.0590	0.0172	0.7044	2.8241	0.0146	0.7907	15
2.9692	0.0177	0.6843	2.7517	0.0149	0.7645	16
2.8783	0.0181	0.6630	2.6682	0.0152	0.7263	17
2.7622	0.0187	0.6417	2.5586	0.0156	0.7220	18
2.6164	0.0194	0.6138	2.4121	0.0161	0.6909	19
2.4405	0.0203	0.5838	2.2417	0.0167	0.6527	20
2.2404	0.0213	0.5486	2.1401	0.0170	0.6662	21
2.0196	0.0225	0.5086	1.8907	0.0180	0.5774	22
1.7917	0.0237	0.4665	1.7073	0.0186	0.5446	23
1.5286	0.0253	0.4182	1.5139	0.0194	0.4919	24
1.2991	0.0267	0.3736	1.3605	0.0200	0.4570	25
1.1117	0.0279	0.3336	1.2304	0.0205	0.4262	26
0.9643	0.0289	0.2986	1.1387	0.0209	0.4040	27
0.8404	0.0298	0.2663	1.0514	0.0213	0.3776	28
0.7408	0.0305	0.2408	0.9883	0.0216	0.3596	29
0.6542	0.0311	0.2155	0.9281	0.0218	0.3418	30
0.5800	0.0316	0.1936	0.8801	0.0221	0.3269	31
0.5168	0.0321	0.1737	0.8401	0.0222	0.3168	32
0.4595	0.0326	0.1552	0.8071	0.0224	0.3077	33
0.4080	0.0330	0.1375	0.7825	0.0225	0.2994	34

bigmorning/whisper_syl_noforce__0035

whisper_syl_noforce__0035