wh_4_sun_syl_w_0_lr_8en5_b32_0030

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: 0.3105
• Train Accuracy: 0.0330
• Train Wermet: 0.0789
• Train Wermet Syl: 0.1339
• Validation Loss: 1.1690
• Validation Accuracy: 0.0207
• Validation Wermet: 0.3261
• Validation Wermet Syl: 0.3084
• Epoch: 29

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': 8e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0}
• training_precision: float32

Training results

Train Loss	Train Accuracy	Train Wermet	Train Wermet Syl	Validation Loss	Validation Accuracy	Validation Wermet	Validation Wermet Syl	Epoch
5.2081	0.0105	1.5151	1.1936	4.0143	0.0113	0.9817	0.9765	0
4.7532	0.0116	0.8756	0.8371	3.9494	0.0114	0.9457	0.9171	1
4.7031	0.0117	0.8615	0.8175	3.9244	0.0114	0.9383	0.8993	2
4.6799	0.0117	0.8569	0.8117	3.9091	0.0114	0.9659	0.9487	3
4.6415	0.0117	0.8450	0.7985	3.8828	0.0115	0.9227	0.8867	4
4.6194	0.0118	0.8366	0.7901	3.8588	0.0115	0.9314	0.8973	5
4.5993	0.0118	0.8253	0.7803	3.9068	0.0116	0.9000	0.8526	6
4.5584	0.0120	0.7864	0.7455	3.7567	0.0118	0.8407	0.7907	7
4.4423	0.0123	0.7655	0.7209	3.5099	0.0123	0.8256	0.7786	8
4.0719	0.0133	0.7479	0.7112	2.9385	0.0135	0.7636	0.7193	9
3.5177	0.0148	0.7049	0.6917	2.4295	0.0148	0.6907	0.6559	10
2.8931	0.0170	0.6532	0.6928	2.0341	0.0161	0.6031	0.5778	11
2.4018	0.0190	0.6050	0.7024	1.7053	0.0174	0.5373	0.5223	12
1.9940	0.0210	0.5579	0.7168	1.5422	0.0180	0.4803	0.4793	13
1.7258	0.0223	0.5356	0.7426	1.4314	0.0186	0.4270	0.4029	14
1.4823	0.0237	0.4865	0.7094	1.3495	0.0190	0.4146	0.4082	15
1.2444	0.0252	0.4278	0.6455	1.2070	0.0198	0.3945	0.3965	16
1.1179	0.0261	0.3774	0.5791	1.1574	0.0200	0.3679	0.3479	17
1.0182	0.0267	0.3377	0.5283	1.3384	0.0189	0.3799	0.3800	18
0.9117	0.0276	0.2949	0.4680	1.2758	0.0192	0.4053	0.4485	19
0.7453	0.0290	0.2613	0.4292	1.1716	0.0203	0.3453	0.3306	20
0.6662	0.0296	0.2193	0.3666	1.1194	0.0205	0.3391	0.3188	21
0.5670	0.0305	0.1841	0.3121	1.2457	0.0200	0.3477	0.3347	22
0.5777	0.0304	0.1711	0.2936	1.2328	0.0201	0.3512	0.3321	23
0.4963	0.0312	0.1340	0.2298	1.4423	0.0189	0.3788	0.3437	24
0.4911	0.0311	0.1337	0.2363	1.1022	0.0208	0.3216	0.3001	25
0.3529	0.0326	0.1065	0.2027	1.1164	0.0209	0.3236	0.2979	26
0.3296	0.0328	0.0915	0.1748	1.1417	0.0208	0.3238	0.3087	27
0.2417	0.0337	0.0661	0.1297	1.1344	0.0210	0.3181	0.2957	28
0.3105	0.0330	0.0789	0.1339	1.1690	0.0207	0.3261	0.3084	29

Framework versions

• Transformers 4.34.0.dev0
• TensorFlow 2.13.0
• Tokenizers 0.13.3