train_from_raw_cv12_true__0050

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: 4.0167
• Validation Loss: 0.4845
• Validation Accuracy: 0.0642
• Validation Wermet: 10.2553
• Epoch: 49

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

Framework versions

• Transformers 4.33.0.dev0
• TensorFlow 2.13.0
• Tokenizers 0.13.3