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wav2vec2-large-xlsr-53-W2V2-TATAR-SMALL

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4714
  • Wer: 0.5316

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
6.2446 1.17 400 3.2621 1.0
1.739 2.35 800 0.5832 0.7688
0.4718 3.52 1200 0.4785 0.6824
0.3574 4.69 1600 0.4814 0.6792
0.2946 5.86 2000 0.4484 0.6506
0.2674 7.04 2400 0.4612 0.6225
0.2349 8.21 2800 0.4600 0.6050
0.2206 9.38 3200 0.4772 0.6048
0.2072 10.56 3600 0.4676 0.6106
0.1984 11.73 4000 0.4816 0.6079
0.1793 12.9 4400 0.4616 0.5836
0.172 14.08 4800 0.4808 0.5860
0.1624 15.25 5200 0.4854 0.5820
0.156 16.42 5600 0.4609 0.5656
0.1448 17.59 6000 0.4926 0.5817
0.1406 18.77 6400 0.4638 0.5654
0.1337 19.94 6800 0.4731 0.5652
0.1317 21.11 7200 0.4861 0.5639
0.1179 22.29 7600 0.4766 0.5521
0.1197 23.46 8000 0.4824 0.5584
0.1096 24.63 8400 0.5006 0.5559
0.1038 25.81 8800 0.4994 0.5440
0.0992 26.98 9200 0.4867 0.5405
0.0984 28.15 9600 0.4798 0.5361
0.0943 29.33 10000 0.4714 0.5316

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.10.0+cu111
  • Datasets 1.14.0
  • Tokenizers 0.10.3
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Dataset used to train emre/wav2vec2-large-xlsr-53-W2V2-TATAR-SMALL

Evaluation results