wh_4_sun_syl_w_0_lr_8en5_b32_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: 4.0719
• Train Accuracy: 0.0133
• Train Wermet: 0.7479
• Train Wermet Syl: 0.7112
• Validation Loss: 2.9385
• Validation Accuracy: 0.0135
• Validation Wermet: 0.7636
• Validation Wermet Syl: 0.7193
• 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': 8e-05, '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
5.2081	0.0105	1.5151	1.1936	4.0143	0.0113	0.9817	0.9765	0
4.7532	0.0116	0.8756	0.8371	3.9494	0.0114	0.9457	0.9171	1
4.7031	0.0117	0.8615	0.8175	3.9244	0.0114	0.9383	0.8993	2
4.6799	0.0117	0.8569	0.8117	3.9091	0.0114	0.9659	0.9487	3
4.6415	0.0117	0.8450	0.7985	3.8828	0.0115	0.9227	0.8867	4
4.6194	0.0118	0.8366	0.7901	3.8588	0.0115	0.9314	0.8973	5
4.5993	0.0118	0.8253	0.7803	3.9068	0.0116	0.9000	0.8526	6
4.5584	0.0120	0.7864	0.7455	3.7567	0.0118	0.8407	0.7907	7
4.4423	0.0123	0.7655	0.7209	3.5099	0.0123	0.8256	0.7786	8
4.0719	0.0133	0.7479	0.7112	2.9385	0.0135	0.7636	0.7193	9

Framework versions

• Transformers 4.34.0.dev0
• TensorFlow 2.13.0
• Tokenizers 0.13.3