vowelizer_1203_v10

This model is a fine-tuned version of Buseak/vowelizer_1203_v9 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0000
• Precision: 1.0000
• Recall: 1.0000
• F1: 1.0000
• Accuracy: 1.0000

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:

• learning_rate: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0383	1.0	967	0.0127	0.9939	0.9893	0.9916	0.9961
0.0237	2.0	1934	0.0064	0.9967	0.9950	0.9959	0.9980
0.016	3.0	2901	0.0039	0.9978	0.9966	0.9972	0.9987
0.0119	4.0	3868	0.0024	0.9987	0.9982	0.9985	0.9993
0.0097	5.0	4835	0.0016	0.9990	0.9989	0.9990	0.9995
0.0078	6.0	5802	0.0012	0.9992	0.9993	0.9992	0.9996
0.0064	7.0	6769	0.0007	0.9996	0.9995	0.9996	0.9998
0.0056	8.0	7736	0.0007	0.9997	0.9996	0.9996	0.9998
0.005	9.0	8703	0.0004	0.9998	0.9997	0.9997	0.9999
0.0042	10.0	9670	0.0004	0.9997	0.9997	0.9997	0.9999
0.0037	11.0	10637	0.0002	0.9999	0.9998	0.9999	0.9999
0.0031	12.0	11604	0.0002	0.9999	0.9999	0.9999	1.0000
0.0026	13.0	12571	0.0001	0.9999	1.0000	0.9999	1.0000
0.0024	14.0	13538	0.0001	0.9999	0.9999	0.9999	1.0000
0.002	15.0	14505	0.0001	1.0000	1.0000	1.0000	1.0000
0.0019	16.0	15472	0.0000	1.0000	1.0000	1.0000	1.0000
0.0017	17.0	16439	0.0000	1.0000	1.0000	1.0000	1.0000
0.0014	18.0	17406	0.0000	1.0000	1.0000	1.0000	1.0000
0.0011	19.0	18373	0.0000	1.0000	1.0000	1.0000	1.0000
0.0012	20.0	19340	0.0000	1.0000	1.0000	1.0000	1.0000

Framework versions

• Transformers 4.28.0
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.13.3