whisper-tiny-finetuned-gtzan

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

• Loss: 0.4916
• Accuracy: 0.91

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:

• learning_rate: 5e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.1202	1.0	57	2.0148	0.49
1.4611	2.0	114	1.3965	0.62
0.9725	3.0	171	0.8726	0.82
0.4971	4.0	228	0.7578	0.76
0.2255	5.0	285	0.7502	0.74
0.2803	6.0	342	0.5457	0.84
0.2234	7.0	399	0.7014	0.8
0.0845	8.0	456	0.4250	0.89
0.0395	9.0	513	0.5069	0.9
0.0438	10.0	570	0.4916	0.91
0.0442	11.0	627	0.7312	0.86
0.002	12.0	684	0.4753	0.9
0.0769	13.0	741	0.8024	0.86
0.0015	14.0	798	0.6354	0.9
0.001	15.0	855	0.5665	0.91
0.0008	16.0	912	0.5537	0.9
0.0009	17.0	969	0.6251	0.88
0.0007	18.0	1026	0.6641	0.9
0.0006	19.0	1083	0.5746	0.9
0.0006	20.0	1140	0.5893	0.9
0.0006	21.0	1197	0.5636	0.91
0.0005	22.0	1254	0.5785	0.91
0.0118	23.0	1311	0.5674	0.91
0.0005	24.0	1368	0.5915	0.91
0.0585	25.0	1425	0.5690	0.91
0.0004	26.0	1482	0.6043	0.9
0.008	27.0	1539	0.5911	0.91
0.0208	28.0	1596	0.5973	0.91
0.0004	29.0	1653	0.6009	0.91
0.0004	30.0	1710	0.6035	0.91

Framework versions

• Transformers 4.29.2
• Pytorch 2.0.0
• Datasets 2.13.1
• Tokenizers 0.13.3