metadata

license: apache-2.0
tags:
  - generated_from_keras_callback
model-index:
  - name: whisper_havest_0035
    results: []

whisper_havest_0035

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

Model description

More information needed

More information needed

More information needed

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

Train Loss	Train Accuracy	Train Do Wer	Validation Loss	Validation Accuracy	Validation Do Wer	Epoch
9.9191	0.0046	1.0	8.5836	0.0067	1.0	0
8.0709	0.0083	1.0	7.4667	0.0089	1.0	1
7.1652	0.0100	1.0	6.8204	0.0112	1.0	2
6.7196	0.0114	1.0	6.5192	0.0114	1.0	3
6.4115	0.0115	1.0	6.2357	0.0115	1.0	4
6.1085	0.0115	1.0	5.9657	0.0115	1.0	5
5.8206	0.0115	1.0	5.7162	0.0115	1.0	6
5.5567	0.0115	1.0	5.4963	0.0115	1.0	7
5.3223	0.0116	1.0	5.3096	0.0116	1.0	8
5.1222	0.0117	1.0	5.1600	0.0117	1.0	9
4.9580	0.0117	1.0	5.0391	0.0118	1.0	10
4.8251	0.0119	1.0	4.9427	0.0118	1.0	11
4.7171	0.0119	1.0	4.8691	0.0119	1.0	12
4.6284	0.0121	1.0	4.8123	0.0120	1.0	13
4.5508	0.0121	1.0	4.7620	0.0121	1.0	14
4.4855	0.0123	1.0	4.7260	0.0121	1.0	15
4.4305	0.0124	1.0	4.7018	0.0123	1.0	16
4.3788	0.0125	1.0	4.6738	0.0123	1.0	17
4.3305	0.0127	1.0	4.6525	0.0124	1.0	18
4.2860	0.0128	1.0	4.6401	0.0125	1.0	19
4.2451	0.0130	1.0	4.6234	0.0126	1.0	20
4.1994	0.0132	1.0	4.6077	0.0128	1.0	21
4.1521	0.0133	1.0	4.6098	0.0129	1.0	22
4.1148	0.0134	1.0	4.5919	0.0129	1.0	23
4.0701	0.0135	1.0	4.6038	0.0128	1.0	24
4.0199	0.0137	1.0	4.5777	0.0130	1.0	25
3.9631	0.0138	1.0	4.5734	0.0131	1.0	26
3.9175	0.0140	1.0	4.5866	0.0129	1.0	27
3.8690	0.0142	1.0	4.5900	0.0129	1.0	28
3.8276	0.0143	1.0	4.5602	0.0131	1.0	29
3.7499	0.0145	1.0	4.5619	0.0132	1.0	30
3.6968	0.0147	1.0	4.6203	0.0133	1.0	31
3.6714	0.0149	1.0	4.7075	0.0133	1.0	32
3.6318	0.0149	1.0	4.6638	0.0125	1.0	33
3.5897	0.0150	1.0	4.5822	0.0130	1.0	34