graduation-reserach-1-demo – AI Model by leviethoang | AlphaNeural AI

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leviethoang/
graduation-reserach-1-demo

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wav2vec2-large-xls-r-300m-vi-25p

This model was trained from scratch on the common_voice dataset. It achieves the following results on the evaluation set:

Loss: 1.8293
Wer: 0.4109

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: 0.0003
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.9542	1.31	400	1.4443	0.5703
1.276	2.62	800	1.4606	0.5736
1.1311	3.93	1200	1.4552	0.5186
0.9519	5.25	1600	1.4477	0.5300
0.8293	6.56	2000	1.4166	0.5097
0.7555	7.87	2400	1.4100	0.4906
0.6724	9.18	2800	1.4982	0.4880
0.6038	10.49	3200	1.4524	0.4945
0.5338	11.8	3600	1.4995	0.4798
0.4988	13.11	4000	1.6715	0.4653
0.461	14.43	4400	1.5699	0.4552
0.4154	15.74	4800	1.5762	0.4557
0.3822	17.05	5200	1.5978	0.4471
0.3466	18.36	5600	1.6579	0.4512
0.3226	19.67	6000	1.6825	0.4378
0.2885	20.98	6400	1.7376	0.4421
0.2788	22.29	6800	1.7150	0.4300
0.249	23.61	7200	1.7073	0.4263
0.2317	24.92	7600	1.7349	0.4200
0.2171	26.23	8000	1.7419	0.4186
0.1963	27.54	8400	1.8438	0.4144
0.1906	28.85	8800	1.8293	0.4109

Framework versions

Transformers 4.11.3
Pytorch 1.10.0+cu113
Datasets 1.18.3
Tokenizers 0.10.3