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
5.6348	0.0091	1.5865	4.2935	0.0093	0.9579	0
4.9212	0.0099	0.9054	4.1262	0.0097	0.9390	1
4.6819	0.0107	0.8319	3.9071	0.0103	0.8966	2
4.4443	0.0114	0.8310	3.7367	0.0106	0.8939	3
4.2479	0.0119	0.8226	3.6101	0.0109	0.8696	4
4.0911	0.0124	0.8103	3.5364	0.0110	0.8946	5
3.9590	0.0127	0.7913	3.4556	0.0113	0.8388	6
3.8513	0.0130	0.7794	3.4106	0.0114	0.8515	7
3.7607	0.0133	0.7657	3.3507	0.0115	0.8261	8
3.6757	0.0136	0.7548	3.3141	0.0116	0.8400	9
3.6023	0.0138	0.7454	3.2711	0.0117	0.8006	10
3.5261	0.0140	0.7348	3.2391	0.0119	0.8101	11
3.4534	0.0143	0.7212	3.2070	0.0120	0.7870	12
3.3814	0.0146	0.7080	3.1505	0.0122	0.7826	13
3.3069	0.0148	0.6961	3.1102	0.0124	0.7609	14
3.2229	0.0152	0.6781	3.0542	0.0125	0.7532	15
3.1334	0.0156	0.6614	2.9840	0.0127	0.7448	16
3.0313	0.0160	0.6425	2.9032	0.0130	0.7123	17
2.9122	0.0166	0.6202	2.7986	0.0134	0.6930	18
2.7559	0.0173	0.5940	2.6337	0.0139	0.6673	19
2.5649	0.0182	0.5674	2.4490	0.0145	0.6383	20
2.3414	0.0193	0.5299	2.2785	0.0150	0.6183	21
2.0966	0.0206	0.4903	2.0460	0.0158	0.5649	22
1.8283	0.0220	0.4459	1.8369	0.0165	0.5306	23
1.5547	0.0235	0.3996	1.6356	0.0172	0.4848	24
1.3218	0.0249	0.3581	1.4682	0.0179	0.4510	25
1.1383	0.0260	0.3211	1.3465	0.0183	0.4226	26
0.9876	0.0270	0.2920	1.2323	0.0188	0.3966	27
0.8635	0.0278	0.2651	1.1482	0.0191	0.3749	28
0.7620	0.0284	0.2435	1.0816	0.0194	0.3565	29

bigmorning/whisper_input_decoder_shift_r_labels_no_force__0030

whisper_input_decoder_shift_r_labels_no_force__0030