Mizo Automatic Speech Recognition (ASR) Models v2.0

wav2vec2-xls-r-1b-mizonal2-lus-v25.03.04

This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the generator dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1761
  • Wer: 0.1620

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: 49
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 12
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.6249 1.31 1000 0.4045 0.4574
0.4758 2.62 2000 0.2601 0.3161
0.3755 3.93 3000 0.2119 0.2553
0.3019 5.24 4000 0.1904 0.2346
0.2391 6.55 5000 0.1819 0.2296
0.1925 7.86 6000 0.1660 0.2022
0.1502 9.17 7000 0.1696 0.1797
0.1128 10.48 8000 0.1810 0.1745
0.0851 11.8 9000 0.1761 0.1620

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.3.1+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1
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Evaluation results