whisper_input_decoder_shift_r_labels_with_force__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: 0.0012
Train Accuracy: 0.0340
Train Wermet: 29.4939
Validation Loss: 0.8115
Validation Accuracy: 0.0210
Validation Wermet: 43.5361
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': 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
5.6249	0.0091	1.7162	4.2965	0.0094	0.9447	0
4.9223	0.0099	0.9041	4.1562	0.0097	0.9327	1
4.6814	0.0107	0.8376	3.9245	0.0103	0.8927	2
4.4407	0.0114	0.8311	3.7252	0.0107	0.8775	3
4.2445	0.0119	0.8228	3.6283	0.0108	0.8695	4
4.0889	0.0123	0.8067	3.5310	0.0110	0.8916	5
3.9575	0.0127	0.7908	3.4478	0.0113	0.8407	6
3.8547	0.0130	0.7781	3.4227	0.0113	0.8670	7
3.7599	0.0133	0.7654	3.3519	0.0115	0.8375	8
3.6763	0.0136	0.7543	3.3183	0.0116	0.8678	9
3.6006	0.0138	0.7421	3.2581	0.0117	0.8120	10
3.5300	0.0140	0.7296	3.2415	0.0118	0.8257	11
3.4554	0.0143	0.7179	3.2163	0.0119	0.8078	12
3.3930	0.0145	0.7057	3.1612	0.0121	0.7758	13
3.3218	0.0148	0.6946	3.1357	0.0122	0.7760	14
3.2424	0.0151	0.6806	3.0812	0.0123	0.7639	15
3.1577	0.0155	0.6633	3.0193	0.0126	0.7428	16
3.0655	0.0159	0.6454	2.9643	0.0128	0.7423	17
2.9579	0.0164	0.6271	2.8510	0.0132	0.7103	18
2.8149	0.0170	0.6022	2.7020	0.0136	0.6811	19
2.6475	0.0178	0.5775	2.5406	0.0142	0.6495	20
2.4340	0.0189	0.5451	2.3364	0.0149	0.6166	21
2.2002	0.0200	0.5065	2.1300	0.0155	0.5766	22
1.9511	0.0213	0.4658	1.9335	0.0162	0.5419	23
1.6777	0.0228	0.4184	1.7327	0.0169	0.5071	24
1.4282	0.0243	0.3754	1.5461	0.0176	0.4669	25
1.2219	0.0255	0.3365	1.4027	0.0181	0.4326	26
1.0535	0.0265	0.3016	1.2979	0.0185	0.4134	27
0.9205	0.0274	0.2731	1.1891	0.0189	0.3843	28
0.8079	0.0281	0.2453	1.1135	0.0192	0.3659	29
0.7140	0.0288	0.2218	1.0532	0.0195	0.3495	30
0.6318	0.0293	0.1975	0.9976	0.0197	0.3351	31
0.5623	0.0298	0.1770	0.9571	0.0199	0.3256	32
0.4990	0.0303	0.1582	0.9184	0.0200	0.3147	33
0.4444	0.0307	0.1424	0.8865	0.0202	0.3062	34
0.3949	0.0311	0.1260	0.8532	0.0203	0.2968	35
0.3505	0.0314	0.1118	0.8333	0.0204	0.2898	36
0.3104	0.0317	0.0988	0.8245	0.0204	0.2881	37
0.2743	0.0321	0.0886	0.8014	0.0205	0.2825	38
0.2428	0.0323	0.0842	0.7944	0.0206	0.2794	39
0.2120	0.0326	0.0880	0.7742	0.0206	0.2762	40
0.1863	0.0328	0.1289	0.7744	0.0206	0.2863	41
0.1621	0.0330	0.1792	0.7683	0.0207	0.2873	42
0.1390	0.0332	0.1918	0.7664	0.0207	0.4006	43
0.1194	0.0334	0.3137	0.7596	0.0207	0.5479	44
0.1022	0.0335	0.5546	0.7607	0.0208	0.8384	45
0.0880	0.0337	0.9275	0.7595	0.0208	0.8106	46
0.0740	0.0338	1.7784	0.7555	0.0208	0.9209	47
0.0622	0.0338	2.6518	0.7572	0.0208	2.2106	48
0.0528	0.0339	2.2627	0.7565	0.0208	1.4870	49
0.0453	0.0339	4.0945	0.7590	0.0208	3.1276	50
0.0407	0.0339	6.6959	0.7542	0.0208	6.1620	51
0.0327	0.0340	7.6116	0.7558	0.0208	8.6756	52
0.0264	0.0340	11.0921	0.7526	0.0209	7.4669	53
0.0222	0.0340	9.9266	0.7573	0.0209	7.1746	54
0.0189	0.0340	10.5104	0.7622	0.0209	8.7817	55
0.0159	0.0340	11.4594	0.7671	0.0209	13.3827	56
0.0134	0.0340	12.9412	0.7711	0.0209	15.0106	57
0.0115	0.0340	14.8090	0.7737	0.0209	13.2722	58
0.0099	0.0340	15.5619	0.7767	0.0209	15.6065	59
0.0086	0.0340	16.8891	0.7814	0.0209	14.4270	60
0.0074	0.0340	19.8526	0.7818	0.0209	23.6084	61
0.0224	0.0339	25.5730	0.7659	0.0209	31.2366	62
0.0171	0.0340	20.4968	0.7611	0.0210	13.3031	63
0.0099	0.0340	13.3312	0.7636	0.0210	8.2061	64
0.0068	0.0340	11.3060	0.7556	0.0210	11.1380	65
0.0053	0.0340	13.2403	0.7613	0.0210	8.9220	66
0.0045	0.0340	13.2371	0.7722	0.0210	14.7377	67
0.0040	0.0340	15.3554	0.7668	0.0210	15.6763	68
0.0035	0.0340	16.6461	0.7735	0.0210	16.8715	69
0.0032	0.0340	18.7469	0.7757	0.0210	18.4540	70
0.0029	0.0340	19.8120	0.7846	0.0210	22.5624	71
0.0026	0.0340	21.6212	0.7821	0.0210	21.7265	72
0.0023	0.0340	22.7740	0.7886	0.0210	26.6152	73
0.0021	0.0340	25.1048	0.7907	0.0210	28.2909	74
0.0019	0.0340	24.5815	0.7949	0.0210	38.3868	75
0.0017	0.0340	27.4132	0.7962	0.0210	31.9349	76
0.0015	0.0340	27.7907	0.8016	0.0210	41.0701	77
0.0013	0.0340	28.5343	0.8074	0.0210	34.6894	78
0.0012	0.0340	29.4939	0.8115	0.0210	43.5361	79

Framework versions

Transformers 4.34.0.dev0
TensorFlow 2.13.0
Tokenizers 0.13.3

whisper_input_decoder_shift_r_labels_with_force__0080

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

NSDT 3DConvert

UnrealSynth

DreamTexture.js