optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-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
5.0233	0.0115	1.6383	3.8616	0.0117	0.9516	0
4.4412	0.0127	0.8560	3.5410	0.0125	0.8971	1
4.0719	0.0138	0.8366	3.2944	0.0132	0.8706	2
3.8091	0.0146	0.8133	3.1691	0.0134	0.8487	3
3.6239	0.0152	0.7866	3.0647	0.0136	0.8282	4
3.4749	0.0156	0.7589	2.9835	0.0139	0.8049	5
3.3444	0.0161	0.7359	2.9351	0.0140	0.7979	6
3.2215	0.0165	0.7138	2.8468	0.0145	0.7589	7
3.0754	0.0172	0.6873	2.7530	0.0148	0.7413	8
2.8713	0.0181	0.6484	2.5226	0.0157	0.7017	9
2.5469	0.0197	0.5934	2.1931	0.0168	0.6285	10
2.0233	0.0225	0.4997	1.6411	0.0189	0.5215	11
1.3808	0.0264	0.3852	1.2401	0.0205	0.4238	12
0.9722	0.0290	0.3123	1.0195	0.0215	0.3682	13
0.7388	0.0305	0.2828	0.8773	0.0221	0.3322	14
0.5787	0.0317	0.2751	0.7970	0.0225	0.3083	15
0.4642	0.0325	0.2878	0.7315	0.0227	0.2964	16
0.3752	0.0332	0.4217	0.6897	0.0229	0.3297	17
0.3042	0.0338	0.7294	0.6572	0.0231	0.4453	18
0.2444	0.0343	1.1298	0.6369	0.0232	0.6637	19
0.1949	0.0348	1.6370	0.6180	0.0233	1.6119	20
0.1544	0.0352	1.6151	0.6149	0.0233	1.6843	21
0.1212	0.0355	1.3832	0.6066	0.0233	0.8721	22
0.0931	0.0357	1.2799	0.6034	0.0234	0.5109	23
0.0725	0.0359	1.0940	0.6102	0.0234	1.0111	24
0.0551	0.0361	1.2865	0.6000	0.0234	1.1393	25
0.0411	0.0361	1.8511	0.6037	0.0235	2.0574	26
0.0311	0.0362	1.7179	0.6018	0.0235	1.4847	27
0.0253	0.0362	0.9801	0.6010	0.0235	0.4457	28
0.0231	0.0362	0.9376	0.6046	0.0235	0.9247	29
0.0196	0.0362	0.6466	0.6078	0.0235	0.5271	30
0.0177	0.0362	0.4041	0.6155	0.0235	0.4352	31
0.0139	0.0362	0.4202	0.6037	0.0236	0.5585	32
0.0137	0.0362	0.8151	0.6015	0.0236	1.8476	33
0.0122	0.0362	3.4515	0.6043	0.0236	3.8210	34

bigmorning/whisper_syl_cv12_pad_lob100__0035

whisper_syl_cv12_pad_lob100__0035