whisper_4_with_init_sun_syl_wd_0_lr_en4_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: 1.0272
• Train Accuracy: 0.0266
• Train Wermet: 0.2339
• Train Wermet Syl: 0.2620
• Validation Loss: 1.0518
• Validation Accuracy: 0.0206
• Validation Wermet: 0.3258
• Validation Wermet Syl: 0.2928
• 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-04, '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
4.9733	0.0111	1.5643	1.4238	3.9610	0.0114	0.9612	0.9404	0
4.6745	0.0116	0.8628	0.8245	3.8859	0.0115	0.9258	0.8928	1
4.6271	0.0117	0.8456	0.8063	3.8727	0.0114	0.9561	0.9364	2
4.5738	0.0119	0.8242	0.8004	3.7410	0.0117	0.8760	0.8375	3
4.1772	0.0130	0.7540	0.7249	2.8900	0.0136	0.7575	0.7119	4
3.1940	0.0159	0.6535	0.6496	2.2086	0.0152	0.6192	0.5859	5
2.3103	0.0193	0.5146	0.5379	1.4923	0.0182	0.4666	0.4350	6
1.6683	0.0226	0.3900	0.4225	1.2258	0.0195	0.3874	0.3520	7
1.2915	0.0248	0.2991	0.3266	1.1613	0.0198	0.3557	0.3195	8
1.0272	0.0266	0.2339	0.2620	1.0518	0.0206	0.3258	0.2928	9

Framework versions

• Transformers 4.34.0.dev0
• TensorFlow 2.13.0
• Tokenizers 0.13.3