whisper_syl_cv12_pad_lob100__0045

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: 0.0028
• Train Accuracy: 0.0362
• Train Wermet: 2.2629
• Validation Loss: 0.6001
• Validation Accuracy: 0.0238
• Validation Wermet: 3.4388
• Epoch: 44

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
5.0233	0.0115	1.6383	3.8616	0.0117	0.9516	0
4.4412	0.0127	0.8560	3.5410	0.0125	0.8971	1
4.0719	0.0138	0.8366	3.2944	0.0132	0.8706	2
3.8091	0.0146	0.8133	3.1691	0.0134	0.8487	3
3.6239	0.0152	0.7866	3.0647	0.0136	0.8282	4
3.4749	0.0156	0.7589	2.9835	0.0139	0.8049	5
3.3444	0.0161	0.7359	2.9351	0.0140	0.7979	6
3.2215	0.0165	0.7138	2.8468	0.0145	0.7589	7
3.0754	0.0172	0.6873	2.7530	0.0148	0.7413	8
2.8713	0.0181	0.6484	2.5226	0.0157	0.7017	9
2.5469	0.0197	0.5934	2.1931	0.0168	0.6285	10
2.0233	0.0225	0.4997	1.6411	0.0189	0.5215	11
1.3808	0.0264	0.3852	1.2401	0.0205	0.4238	12
0.9722	0.0290	0.3123	1.0195	0.0215	0.3682	13
0.7388	0.0305	0.2828	0.8773	0.0221	0.3322	14
0.5787	0.0317	0.2751	0.7970	0.0225	0.3083	15
0.4642	0.0325	0.2878	0.7315	0.0227	0.2964	16
0.3752	0.0332	0.4217	0.6897	0.0229	0.3297	17
0.3042	0.0338	0.7294	0.6572	0.0231	0.4453	18
0.2444	0.0343	1.1298	0.6369	0.0232	0.6637	19
0.1949	0.0348	1.6370	0.6180	0.0233	1.6119	20
0.1544	0.0352	1.6151	0.6149	0.0233	1.6843	21
0.1212	0.0355	1.3832	0.6066	0.0233	0.8721	22
0.0931	0.0357	1.2799	0.6034	0.0234	0.5109	23
0.0725	0.0359	1.0940	0.6102	0.0234	1.0111	24
0.0551	0.0361	1.2865	0.6000	0.0234	1.1393	25
0.0411	0.0361	1.8511	0.6037	0.0235	2.0574	26
0.0311	0.0362	1.7179	0.6018	0.0235	1.4847	27
0.0253	0.0362	0.9801	0.6010	0.0235	0.4457	28
0.0231	0.0362	0.9376	0.6046	0.0235	0.9247	29
0.0196	0.0362	0.6466	0.6078	0.0235	0.5271	30
0.0177	0.0362	0.4041	0.6155	0.0235	0.4352	31
0.0139	0.0362	0.4202	0.6037	0.0236	0.5585	32
0.0137	0.0362	0.8151	0.6015	0.0236	1.8476	33
0.0122	0.0362	3.4515	0.6043	0.0236	3.8210	34
0.0098	0.0362	1.1787	0.5985	0.0236	0.8094	35
0.0071	0.0362	0.9920	0.5992	0.0236	0.8755	36
0.0055	0.0362	2.4665	0.6047	0.0236	2.0127	37
0.0124	0.0362	4.2468	0.6089	0.0236	2.8886	38
0.0109	0.0362	2.0177	0.6097	0.0236	0.3417	39
0.0073	0.0362	0.9927	0.6057	0.0237	2.5519	40
0.0080	0.0362	1.7341	0.6099	0.0236	1.3119	41
0.0063	0.0362	2.4288	0.6058	0.0237	1.3465	42
0.0038	0.0362	1.4535	0.6022	0.0237	1.6804	43
0.0028	0.0362	2.2629	0.6001	0.0238	3.4388	44

Framework versions

• Transformers 4.33.0.dev0
• TensorFlow 2.13.0
• Tokenizers 0.13.3