wav2vec2-base-finetuned-common_voice – AI Model by aydink | AlphaNeural AI

You can deploy this model and start earning money today!

aydink/
wav2vec2-base-finetuned-common_voice

like

0

audio-classification

generated_from_trainer

facebook/wav2vec2-base

endpoints_compatible

Views

No views yet

wav2vec2-base-finetuned-common_voice

This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0560
Accuracy: 0.99
F1: 0.9900
Recall: 0.99
Precision: 0.9902
Mcc: 0.9875
Auc: 0.9983

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: 3e-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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Recall	Precision	Mcc	Auc
0.7394	1.0	200	0.2528	0.95	0.9497	0.95	0.9554	0.9390	0.9952
0.0013	2.0	400	0.0069	0.9975	0.9975	0.9975	0.9975	0.9969	1.0
0.0435	3.0	600	0.0962	0.985	0.9850	0.9850	0.9852	0.9813	0.9987
0.1172	4.0	800	0.0434	0.995	0.9950	0.9950	0.9950	0.9938	0.9993
0.0005	5.0	1000	0.0496	0.9925	0.9925	0.9925	0.9926	0.9906	0.9984
0.0006	6.0	1200	0.0652	0.99	0.9900	0.99	0.9901	0.9875	0.9991
0.0004	7.0	1400	0.0267	0.9975	0.9975	0.9975	0.9975	0.9969	0.9982
0.0003	8.0	1600	0.0423	0.9925	0.9925	0.9925	0.9926	0.9906	0.9982
0.0003	9.0	1800	0.0549	0.9875	0.9875	0.9875	0.9877	0.9844	0.9982
0.0003	10.0	2000	0.0560	0.99	0.9900	0.99	0.9902	0.9875	0.9983

Framework versions

Transformers 4.41.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1