whisper_4_with_init_sun_syl_wd_0_lr_en3_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: 4.1520
• Train Accuracy: 0.0126
• Train Wermet: 1.7418
• Train Wermet Syl: 2.3436
• Validation Loss: 3.2869
• Validation Accuracy: 0.0124
• Validation Wermet: 1.3462
• Validation Wermet Syl: 1.8561
• 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': 0.001, '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
5.0580	0.0110	1.8635	1.7118	4.0077	0.0112	1.0399	1.0195	0
4.7330	0.0115	0.9446	0.9262	3.9889	0.0113	0.9757	0.9619	1
4.6832	0.0116	0.8889	0.8637	3.9832	0.0114	0.9574	0.9276	2
4.6668	0.0116	0.9362	0.9592	3.9389	0.0113	0.9939	1.0310	3
4.6252	0.0117	1.0167	1.1679	3.9158	0.0114	0.9633	0.9764	4
4.6026	0.0117	1.0596	1.2533	3.8896	0.0114	0.9953	1.0541	5
4.5658	0.0118	1.1222	1.3998	3.8228	0.0116	0.9368	0.9177	6
4.4715	0.0120	1.0840	1.3327	3.7310	0.0117	0.9284	0.9338	7
4.3515	0.0122	1.5346	2.0632	3.6182	0.0119	0.9122	0.9112	8
4.1520	0.0126	1.7418	2.3436	3.2869	0.0124	1.3462	1.8561	9

Framework versions

• Transformers 4.34.0.dev0
• TensorFlow 2.13.0
• Tokenizers 0.13.3