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
0.7688	0.0332	32.0424	0.0164	0.0265	57.8712	0
0.0114	0.0362	31.1067	0.0062	0.0266	54.8371	1
0.0048	0.0362	27.0610	0.0030	0.0266	50.1428	2
0.0027	0.0362	24.9672	0.0018	0.0266	48.0741	3
0.0018	0.0362	23.1500	0.0013	0.0266	44.9304	4
0.0013	0.0362	21.5445	0.0010	0.0266	42.3508	5
0.0009	0.0362	20.2775	0.0008	0.0266	40.4061	6
0.0007	0.0362	19.5082	0.0006	0.0266	38.2329	7
0.0005	0.0362	17.9967	0.0005	0.0266	35.9761	8
0.0004	0.0362	16.8461	0.0004	0.0266	34.1220	9
0.0003	0.0362	15.8373	0.0004	0.0266	32.0054	10
0.0003	0.0362	14.7685	0.0004	0.0266	29.6994	11
0.0002	0.0362	13.4142	0.0003	0.0266	27.1796	12
0.0002	0.0362	12.4809	0.0003	0.0266	25.3421	13
0.0002	0.0362	11.2286	0.0003	0.0266	23.1619	14
0.0001	0.0362	10.2408	0.0003	0.0266	21.3348	15
0.0001	0.0362	9.5439	0.0002	0.0266	20.1758	16
0.0001	0.0362	8.7578	0.0002	0.0266	18.3977	17
0.0001	0.0362	7.8698	0.0002	0.0266	16.2156	18
0.0001	0.0362	7.0007	0.0002	0.0266	14.7919	19
0.0001	0.0362	6.2610	0.0002	0.0266	13.0212	20
0.0001	0.0362	5.5103	0.0002	0.0266	11.5619	21
0.0000	0.0362	4.9163	0.0002	0.0266	10.4626	22
0.0000	0.0362	4.3166	0.0002	0.0266	9.2446	23
0.0000	0.0362	3.7524	0.0002	0.0266	7.7431	24

bigmorning/whisper_input_decoder_equal_labels_no_force__0025

whisper_input_decoder_equal_labels_no_force__0025