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

Training results

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
2.0315	0.0211	0.4978	1.6755	0.0177	0.5084	25
1.9066	0.0217	0.4773	1.6534	0.0178	0.4947	26
1.8279	0.0221	0.4596	1.5606	0.0182	0.4788	27
1.7325	0.0227	0.4412	1.5173	0.0184	0.4667	28
1.6416	0.0232	0.4199	1.4733	0.0186	0.4511	29
1.5702	0.0236	0.4028	1.4519	0.0187	0.4442	30
1.4787	0.0241	0.3839	1.4213	0.0188	0.4322	31
1.4238	0.0244	0.3700	1.3971	0.0190	0.4272	32
1.3561	0.0249	0.3594	1.3499	0.0192	0.4171	33
1.2828	0.0254	0.3431	1.3555	0.0192	0.4097	34
1.2318	0.0257	0.3277	1.3183	0.0194	0.4035	35
1.1668	0.0262	0.3201	1.3068	0.0195	0.3978	36
1.1571	0.0261	0.3105	1.2901	0.0195	0.3916	37
1.0812	0.0267	0.2989	1.2720	0.0197	0.3860	38
1.0134	0.0273	0.2863	1.2593	0.0197	0.3777	39
0.9986	0.0273	0.2769	1.2629	0.0198	0.3754	40
0.9322	0.0279	0.2653	1.2320	0.0199	0.3694	41
0.9021	0.0281	0.2552	1.2308	0.0200	0.3651	42
0.8583	0.0284	0.2444	1.2199	0.0200	0.3614	43
0.8101	0.0288	0.2355	1.2120	0.0200	0.3597	44
0.8045	0.0288	0.2299	1.2023	0.0201	0.3567	45
0.7823	0.0290	0.2213	1.2075	0.0201	0.3529	46
0.7186	0.0296	0.2107	1.1917	0.0202	0.3530	47
0.6949	0.0298	0.2028	1.1926	0.0202	0.3465	48
0.6669	0.0300	0.1943	1.1902	0.0203	0.3446	49
0.6125	0.0305	0.1842	1.1892	0.0203	0.3437	50
0.5926	0.0307	0.1778	1.2058	0.0203	0.3450	51
0.6055	0.0305	0.1738	1.1859	0.0203	0.3394	52
0.5828	0.0307	0.1653	1.1921	0.0203	0.3379	53
0.5507	0.0311	0.1569	1.1906	0.0204	0.3385	54

Framework versions

Transformers 4.33.0.dev0
TensorFlow 2.13.0
Tokenizers 0.13.3

bigmorning/whisper_input_decoder_no_lob__0055

whisper_input_decoder_no_lob__0055

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

bigmorning/
whisper_input_decoder_no_lob__0055