whisper_4_with_init_sun_syl_wd_0_lr_3en4_0010

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: 1.2715
• Train Accuracy: 0.0246
• Train Wermet: 0.5866
• Train Wermet Syl: 0.8432
• Validation Loss: 1.2543
• Validation Accuracy: 0.0196
• Validation Wermet: 0.4646
• Validation Wermet Syl: 0.5397
• Epoch: 9

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': 0.0003, '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
4.9621	0.0111	1.3737	1.2531	3.9542	0.0114	0.9773	0.9699	0
4.6813	0.0116	0.9321	0.9542	3.9070	0.0114	0.9669	0.9552	1
4.6267	0.0117	0.9053	0.9424	3.9109	0.0114	0.9465	0.9128	2
4.5866	0.0118	0.8961	0.9453	3.8787	0.0115	0.9210	0.8988	3
4.5246	0.0119	0.9086	1.0238	3.8947	0.0113	0.9346	0.8618	4
4.0723	0.0131	0.9445	1.1479	2.8783	0.0135	0.8293	0.9656	5
2.9304	0.0167	1.1693	1.7199	1.7990	0.0168	0.5867	0.6425	6
2.0844	0.0201	0.8414	1.1849	1.5133	0.0180	0.5178	0.5473	7
1.6228	0.0225	0.7801	1.0964	1.3701	0.0189	0.4690	0.5092	8
1.2715	0.0246	0.5866	0.8432	1.2543	0.0196	0.4646	0.5397	9

Framework versions

• Transformers 4.34.0.dev0
• TensorFlow 2.13.0
• Tokenizers 0.13.3