whisper_4_with_init_sun_syl_wd_0_lr_en2_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: 4.8685
• Train Accuracy: 0.0113
• Train Wermet: 0.9890
• Train Wermet Syl: 0.9897
• Validation Loss: 4.1857
• Validation Accuracy: 0.0113
• Validation Wermet: 0.9851
• Validation Wermet Syl: 0.9843
• 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': 0.01, '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
39.6121	0.0057	33.2649	25.5768	4.5339	0.0113	0.9851	0.9843	0
5.3698	0.0107	12.0116	9.0545	4.3408	0.0112	0.9919	0.9915	1
5.1979	0.0109	9.4008	7.1909	4.2108	0.0113	0.9851	0.9843	2
5.0669	0.0110	7.0382	5.3339	4.1662	0.0113	0.9851	0.9843	3
4.9546	0.0111	4.8506	3.7351	4.3022	0.0112	0.9870	0.9854	4
4.9453	0.0111	3.9228	3.1750	4.1194	0.0113	0.9851	0.9843	5
4.9123	0.0112	2.2402	1.9643	4.1865	0.0112	1.0000	1.0000	6
4.8957	0.0112	1.7673	1.5892	4.1150	0.0112	1.0000	0.9999	7
4.8959	0.0112	2.2166	1.9601	4.1185	0.0113	0.9851	0.9843	8
4.8685	0.0113	0.9890	0.9897	4.1857	0.0113	0.9851	0.9843	9

Framework versions

• Transformers 4.34.0.dev0
• TensorFlow 2.13.0
• Tokenizers 0.13.3