train_from_raw_cv12_true__0080

This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 0.0024
Train Accuracy: 0.1115
Train Wermet: 4.0259
Validation Loss: 0.5122
Validation Accuracy: 0.0646
Validation Wermet: 9.9376
Epoch: 79

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

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

Training results

Train Loss	Train Accuracy	Train Wermet	Validation Loss	Validation Accuracy	Validation Wermet	Epoch
2.3396	0.0444	2.7124	1.8124	0.0331	9.4418	0
1.7496	0.0562	3.2708	1.6529	0.0359	9.7805	1
1.6254	0.0594	3.1714	1.5874	0.0371	10.4139	2
1.5490	0.0615	3.0208	1.5102	0.0382	8.2054	3
1.4910	0.0631	2.8298	1.4213	0.0402	8.9930	4
1.4233	0.0650	2.7100	1.3319	0.0421	8.8483	5
1.3203	0.0679	2.5125	1.1806	0.0450	7.0373	6
1.1453	0.0730	2.5001	1.0029	0.0484	5.7328	7
0.9537	0.0789	2.6295	0.7799	0.0529	6.7373	8
0.7822	0.0844	2.7501	0.6499	0.0556	8.5538	9
0.6317	0.0895	2.9507	0.5467	0.0578	8.4990	10
0.5010	0.0940	3.1604	0.4597	0.0597	9.4002	11
0.4026	0.0975	3.2910	0.3984	0.0610	9.8173	12
0.3372	0.0998	3.5302	0.3571	0.0619	9.6433	13
0.2922	0.1013	3.5614	0.3391	0.0623	9.6152	14
0.2572	0.1025	3.5685	0.3157	0.0628	9.4497	15
0.2258	0.1036	3.5179	0.3104	0.0630	9.7735	16
0.1995	0.1045	3.5362	0.2944	0.0634	9.8154	17
0.1762	0.1054	3.5227	0.2820	0.0637	9.8672	18
0.1551	0.1061	3.5489	0.2849	0.0638	9.6569	19
0.1356	0.1068	3.4990	0.2821	0.0639	9.9735	20
0.1174	0.1074	3.5119	0.2841	0.0640	9.8770	21
0.1016	0.1080	3.5233	0.2903	0.0640	10.0309	22
0.0847	0.1087	3.5368	0.3013	0.0640	9.8095	23
0.0713	0.1092	3.5250	0.3040	0.0640	9.7686	24
0.0596	0.1096	3.5310	0.3137	0.0640	9.9239	25
0.0478	0.1101	3.5776	0.3228	0.0641	10.2774	26
0.0400	0.1104	3.6155	0.3316	0.0641	9.9082	27
0.0301	0.1107	3.6545	0.3446	0.0641	9.9672	28
0.0227	0.1110	3.7827	0.3579	0.0641	10.2859	29
0.0179	0.1112	3.7672	0.3728	0.0640	10.1965	30
0.0148	0.1112	3.7575	0.3829	0.0641	10.5114	31
0.0116	0.1113	3.7682	0.3959	0.0641	10.4941	32
0.0100	0.1114	3.8332	0.4056	0.0641	10.6330	33
0.0140	0.1112	3.8661	0.4283	0.0638	10.5741	34
0.0159	0.1111	3.8054	0.4203	0.0640	10.5108	35
0.0085	0.1114	3.7278	0.4236	0.0641	10.3731	36
0.0052	0.1115	3.8251	0.4366	0.0641	10.5728	37
0.0058	0.1115	3.9767	0.4459	0.0641	10.5720	38
0.0074	0.1114	4.0721	0.4775	0.0637	10.9922	39
0.0133	0.1111	3.9087	0.4560	0.0640	9.8398	40
0.0072	0.1114	3.9828	0.4533	0.0642	10.7116	41
0.0045	0.1115	3.9705	0.4668	0.0641	10.9326	42
0.0050	0.1114	4.1288	0.4677	0.0641	10.5865	43
0.0057	0.1114	4.1164	0.4709	0.0642	10.9947	44
0.0148	0.1111	4.2062	0.4594	0.0643	10.5855	45
0.0053	0.1114	4.0964	0.4598	0.0644	10.9385	46
0.0024	0.1115	4.1318	0.4660	0.0644	11.2717	47
0.0018	0.1115	4.1024	0.4696	0.0644	11.0203	48
0.0024	0.1115	4.0167	0.4845	0.0642	10.2553	49
0.0065	0.1114	4.1337	0.5009	0.0640	10.6290	50
0.0085	0.1113	4.1551	0.4943	0.0642	10.7108	51
0.0051	0.1114	4.2572	0.4838	0.0644	11.0773	52
0.0029	0.1115	4.2158	0.4869	0.0644	10.8471	53
0.0029	0.1115	4.2389	0.4904	0.0644	10.9344	54
0.0076	0.1114	4.4629	0.5367	0.0637	10.0070	55
0.0109	0.1112	3.8409	0.4880	0.0644	10.0557	56
0.0026	0.1115	3.8716	0.4823	0.0645	10.3257	57
0.0014	0.1115	3.8076	0.4879	0.0645	10.2943	58
0.0008	0.1115	3.8851	0.4854	0.0646	10.3687	59
0.0009	0.1115	3.9626	0.5204	0.0643	10.2350	60
0.0114	0.1111	4.0524	0.4985	0.0643	10.5375	61
0.0051	0.1114	4.0766	0.4958	0.0645	10.3052	62
0.0022	0.1115	4.2414	0.4972	0.0645	10.6064	63
0.0018	0.1115	4.5264	0.5014	0.0645	10.4899	64
0.0033	0.1115	4.4869	0.5182	0.0644	9.8788	65
0.0048	0.1114	4.2916	0.5082	0.0644	10.8155	66
0.0039	0.1114	4.5326	0.5101	0.0644	12.0401	67
0.0025	0.1115	4.4297	0.5056	0.0645	10.9017	68
0.0025	0.1115	4.2703	0.5064	0.0646	11.1319	69
0.0018	0.1115	4.2014	0.5228	0.0644	10.4356	70
0.0046	0.1114	4.1774	0.5267	0.0644	11.5421	71
0.0070	0.1113	4.0521	0.5185	0.0644	11.1608	72
0.0045	0.1114	4.2080	0.5041	0.0646	10.4894	73
0.0018	0.1115	4.1639	0.5001	0.0647	10.9893	74
0.0012	0.1115	4.2831	0.5026	0.0647	11.1654	75
0.0026	0.1115	4.4333	0.5219	0.0645	11.3173	76
0.0056	0.1114	4.1342	0.5351	0.0643	10.6952	77
0.0045	0.1114	4.2413	0.5161	0.0645	10.2386	78
0.0024	0.1115	4.0259	0.5122	0.0646	9.9376	79

Framework versions

Transformers 4.33.0.dev0
TensorFlow 2.13.0
Tokenizers 0.13.3

train_from_raw_cv12_true__0080

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

NSDT 3DConvert

UnrealSynth

DreamTexture.js