vowelizer_1203_v9

This model is a fine-tuned version of Buseak/vowelizer_1203_v6 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
0.0516	1.0	967	0.0195	0.9907	0.9827	0.9867	0.9941
0.0318	2.0	1934	0.0109	0.9950	0.9901	0.9925	0.9967
0.0225	3.0	2901	0.0065	0.9960	0.9950	0.9955	0.9980
0.017	4.0	3868	0.0037	0.9981	0.9968	0.9975	0.9988
0.013	5.0	4835	0.0026	0.9986	0.9980	0.9983	0.9992
0.0103	6.0	5802	0.0018	0.9989	0.9988	0.9989	0.9995
0.0091	7.0	6769	0.0012	0.9992	0.9990	0.9991	0.9996
0.0073	8.0	7736	0.0009	0.9994	0.9992	0.9993	0.9997
0.0065	9.0	8703	0.0006	0.9996	0.9996	0.9996	0.9998
0.0057	10.0	9670	0.0004	0.9997	0.9997	0.9997	0.9999
0.0045	11.0	10637	0.0003	0.9997	0.9997	0.9997	0.9999
0.004	12.0	11604	0.0003	0.9999	0.9998	0.9998	0.9999
0.0035	13.0	12571	0.0002	0.9998	0.9998	0.9998	0.9999
0.003	14.0	13538	0.0002	0.9999	0.9999	0.9999	1.0000
0.0029	15.0	14505	0.0001	0.9999	0.9999	0.9999	1.0000
0.0024	16.0	15472	0.0001	1.0000	0.9999	0.9999	1.0000
0.0021	17.0	16439	0.0001	0.9999	0.9999	0.9999	1.0000
0.0019	18.0	17406	0.0001	1.0000	1.0000	1.0000	1.0000
0.0018	19.0	18373	0.0000	1.0000	1.0000	1.0000	1.0000
0.0015	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