whisper_wermet_nosup_0015

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: 0.2198
• Train Accuracy: 0.0320
• Train Wermet: 3.8215
• Validation Loss: 0.4835
• Validation Accuracy: 0.0311
• Validation Wermet: 4.4217
• Epoch: 14

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
0.4011	0.0307	4.4178	0.5673	0.0306	3.5806	10
0.3446	0.0311	4.1189	0.5329	0.0308	4.7372	11
0.2968	0.0314	3.9189	0.5138	0.0309	2.2499	12
0.2553	0.0317	3.7758	0.4990	0.0310	3.3427	13
0.2198	0.0320	3.8215	0.4835	0.0311	4.4217	14

Framework versions

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