whisper_wermet_nosup_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: 0.4694
• Train Accuracy: 0.0303
• Train Wermet: 4.3895
• Validation Loss: 0.6038
• Validation Accuracy: 0.0304
• Validation Wermet: 2.8294
• 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': 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

Training results

Train Loss	Train Accuracy	Train Wermet	Validation Loss	Validation Accuracy	Validation Wermet	Epoch
5.0729	0.0113	42.1824	4.4421	0.0120	27.3059	0
4.3249	0.0126	23.9224	4.0443	0.0141	18.2054	1
3.8845	0.0144	12.7780	3.4577	0.0169	10.3356	2
2.7411	0.0198	15.0018	1.8774	0.0244	14.5666	3
1.5621	0.0250	9.7248	1.2443	0.0273	5.4731	4
1.0745	0.0272	7.1512	0.9802	0.0285	4.4745	5
0.8261	0.0284	6.2358	0.8209	0.0293	5.6600	6
0.6673	0.0292	5.8338	0.7182	0.0298	4.0874	7
0.5548	0.0298	5.0555	0.6489	0.0301	4.4537	8
0.4694	0.0303	4.3895	0.6038	0.0304	2.8294	9

Framework versions

• Transformers 4.27.0.dev0
• TensorFlow 2.11.0
• Datasets 2.10.0
• Tokenizers 0.13.2