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wav2vec2-common_voice-tr-demo

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

  • Loss: 0.5528
  • Wer: 0.3811

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: 15.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 0.74 100 3.4444 1.0
No log 1.47 200 2.9421 1.0
No log 2.21 300 2.2802 1.0137
No log 2.94 400 0.9683 0.7611
3.7264 3.68 500 0.7941 0.6594
3.7264 4.41 600 0.6695 0.5751
3.7264 5.15 700 0.6507 0.5314
3.7264 5.88 800 0.5731 0.4927
3.7264 6.62 900 0.5723 0.4580
0.4592 7.35 1000 0.5913 0.4479
0.4592 8.09 1100 0.5562 0.4423
0.4592 8.82 1200 0.5566 0.4292
0.4592 9.56 1300 0.5492 0.4303
0.4592 10.29 1400 0.5665 0.4331
0.2121 11.03 1500 0.5610 0.4084
0.2121 11.76 1600 0.5703 0.4014
0.2121 12.5 1700 0.5669 0.3898
0.2121 13.24 1800 0.5586 0.3962
0.2121 13.97 1900 0.5656 0.3897
0.1326 14.71 2000 0.5565 0.3813

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.1+cu113
  • Datasets 1.18.0
  • Tokenizers 0.10.3
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Dataset used to train birgermoell/wav2vec2-common_voice-tr-demo