wh_4_sun_syl_w_0_lr_2en4_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: 4.3967
• Train Accuracy: 0.0123
• Train Wermet: 0.9533
• Train Wermet Syl: 1.1468
• Validation Loss: 3.3131
• Validation Accuracy: 0.0126
• Validation Wermet: 0.8398
• Validation Wermet Syl: 0.8514
• 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': 0.0002, '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
5.2282	0.0106	3.5001	2.7069	4.0241	0.0114	0.9693	0.9528	0
4.7449	0.0116	0.8928	0.8621	3.9408	0.0114	0.9623	0.9431	1
4.7110	0.0116	0.9319	0.9494	4.0066	0.0114	0.9466	0.9714	2
4.6727	0.0117	0.9059	0.9227	3.9101	0.0114	0.9428	0.9156	3
4.6540	0.0117	0.9103	0.9487	3.9216	0.0115	0.9358	0.9594	4
4.6333	0.0117	0.9864	1.1325	3.9306	0.0115	0.9255	0.9484	5
4.6176	0.0117	0.9803	1.1203	3.9175	0.0115	0.9420	0.9530	6
4.5944	0.0118	1.0060	1.1999	3.8546	0.0115	0.9307	0.9259	7
4.5516	0.0119	0.9620	1.1243	3.7716	0.0117	0.8963	0.9090	8
4.3967	0.0123	0.9533	1.1468	3.3131	0.0126	0.8398	0.8514	9

Framework versions

• Transformers 4.34.0.dev0
• TensorFlow 2.13.0
• Tokenizers 0.13.3