whisper_final_09

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: 0.0816
• Train Accuracy: 0.0343
• Validation Loss: 0.5877
• Validation Accuracy: 0.0313
• Epoch: 24

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-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: float32

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
5.0832	0.0116	4.4298	0.0124	0
4.3130	0.0131	4.0733	0.0141	1
3.9211	0.0146	3.6762	0.0157	2
3.5505	0.0159	3.3453	0.0171	3
3.1592	0.0175	2.8062	0.0199	4
2.2581	0.0220	1.7622	0.0252	5
1.4671	0.0259	1.2711	0.0276	6
1.0779	0.0278	1.0220	0.0288	7
0.8591	0.0290	0.8836	0.0295	8
0.7159	0.0297	0.7918	0.0300	9
0.6105	0.0304	0.7276	0.0303	10
0.5287	0.0309	0.6850	0.0306	11
0.4614	0.0313	0.6472	0.0308	12
0.4049	0.0317	0.6199	0.0310	13
0.3562	0.0320	0.6019	0.0311	14
0.3139	0.0324	0.5868	0.0311	15
0.2766	0.0326	0.5751	0.0312	16
0.2438	0.0329	0.5701	0.0312	17
0.2116	0.0332	0.5686	0.0313	18
0.1844	0.0334	0.5619	0.0313	19
0.1593	0.0336	0.5710	0.0313	20
0.1363	0.0338	0.5656	0.0314	21
0.1160	0.0340	0.5763	0.0313	22
0.0981	0.0341	0.5806	0.0313	23
0.0816	0.0343	0.5877	0.0313	24

Framework versions

• Transformers 4.25.0.dev0
• TensorFlow 2.9.2
• Datasets 2.6.1
• Tokenizers 0.13.2