train_from_raw_cv12_true_suppress__0020

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: 0.1762
• Train Accuracy: 0.1054
• Train Wermet: 4.0727
• Validation Loss: 0.2885
• Validation Accuracy: 0.0636
• Validation Wermet: 9.9926
• Epoch: 19

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': 2e-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	Train Wermet	Validation Loss	Validation Accuracy	Validation Wermet	Epoch
2.3569	0.0439	2.6429	1.7869	0.0339	10.1374	0
1.7502	0.0561	3.2762	1.6607	0.0360	9.6159	1
1.6268	0.0595	3.0493	1.5698	0.0374	8.6767	2
1.5533	0.0614	2.3917	1.4965	0.0387	7.2278	3
1.4953	0.0631	1.8208	1.4549	0.0397	4.4667	4
1.4388	0.0647	1.7488	1.3669	0.0411	6.2695	5
1.3532	0.0670	1.6950	1.2392	0.0438	7.1167	6
1.2122	0.0710	1.6785	1.0705	0.0471	4.7509	7
1.0193	0.0768	1.8537	0.9080	0.0502	5.7317	8
0.8466	0.0823	2.3126	0.7098	0.0543	5.7454	9
0.7039	0.0870	2.3440	0.5934	0.0567	6.9383	10
0.5754	0.0914	2.3564	0.5071	0.0586	6.6276	11
0.4749	0.0949	2.6925	0.4391	0.0601	6.8169	12
0.3910	0.0978	3.0462	0.3908	0.0612	8.1284	13
0.3311	0.0999	3.3402	0.3658	0.0617	8.6094	14
0.2871	0.1015	3.4893	0.3344	0.0624	9.6494	15
0.2515	0.1027	3.6567	0.3234	0.0627	9.4059	16
0.2233	0.1037	3.8196	0.3058	0.0631	9.6761	17
0.1980	0.1046	3.9329	0.2916	0.0634	9.8163	18
0.1762	0.1054	4.0727	0.2885	0.0636	9.9926	19

Framework versions

• Transformers 4.33.0.dev0
• TensorFlow 2.13.0
• Tokenizers 0.13.3