This model is a fine-tuned version of daila/wav2vec2-large-xls-r-300m-vi-colab on the common_voice_16_1 dataset. It achieves the following results on the evaluation set:

Loss: 1.6432
Wer: 0.5895

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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
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
0.0916	4.52	400	1.5440	0.6357
0.1344	9.04	800	1.6043	0.6543
0.0926	13.56	1200	1.7226	0.6365
0.0703	18.08	1600	1.5989	0.6048
0.0557	22.6	2000	1.6714	0.6001
0.051	27.12	2400	1.6432	0.5895

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1