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
5.4122	0.0107	0.9328	3.9759	0.0114	0.9606	0
4.7176	0.0116	0.8683	3.9404	0.0114	0.9334	1
4.6750	0.0117	0.8478	3.9211	0.0115	0.9237	2
4.6511	0.0117	0.8413	3.8864	0.0115	0.9331	3
4.6294	0.0118	0.8270	3.8729	0.0115	0.9228	4
4.6134	0.0118	0.8199	3.8690	0.0114	0.9451	5
4.5980	0.0118	0.8102	3.8491	0.0115	0.9152	6
4.5759	0.0119	0.7890	3.8366	0.0116	0.8691	7
4.5518	0.0120	0.7694	3.8081	0.0116	0.9013	8
4.5219	0.0121	0.7591	3.7734	0.0118	0.8383	9
4.4761	0.0122	0.7400	3.7156	0.0120	0.8125	10
4.4139	0.0125	0.7257	3.6311	0.0121	0.8188	11
4.3113	0.0128	0.7127	3.5089	0.0124	0.8008	12
4.1608	0.0132	0.7088	3.3587	0.0127	0.7742	13
3.9595	0.0138	0.7012	3.1493	0.0132	0.7718	14
3.7188	0.0145	0.6820	2.8784	0.0139	0.7292	15
3.4775	0.0153	0.6678	2.6716	0.0144	0.7074	16
3.2575	0.0160	0.6481	2.4980	0.0149	0.6764	17
3.0615	0.0167	0.6314	2.3456	0.0153	0.6476	18
2.8715	0.0174	0.6094	2.2090	0.0158	0.6210	19
2.6930	0.0181	0.5931	2.0918	0.0162	0.5992	20
2.5383	0.0187	0.5739	1.9769	0.0166	0.5791	21
2.3952	0.0193	0.5512	1.9042	0.0168	0.5589	22
2.2427	0.0201	0.5333	1.8028	0.0172	0.5394	23
2.1236	0.0206	0.5174	1.7434	0.0174	0.5240	24

bigmorning/whisper_input_decoder_no_lob__0025

whisper_input_decoder_no_lob__0025