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anton-l/wav2vec2-xls-r-common_voice-tr-ft-stream

🤗 Hugging Face sourceautomatic-speech-recognitionapache-2.014 GBother✓ 5 checksumsupdated today
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wav2vec2-xls-r-common_voice-tr-ft-stream

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3519
  • Wer: 0.2927
  • Cer: 0.0694

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: 0.0005
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.6768 9.01 500 0.4220 0.5143 0.1235
0.3801 19.01 1000 0.3303 0.4403 0.1055
0.3616 29.0 1500 0.3540 0.3716 0.0878
0.2334 39.0 2000 0.3666 0.3671 0.0842
0.3141 49.0 2500 0.3407 0.3373 0.0819
0.1926 58.01 3000 0.3886 0.3520 0.0867
0.1372 68.01 3500 0.3415 0.3189 0.0743
0.091 78.0 4000 0.3750 0.3164 0.0757
0.0893 88.0 4500 0.3559 0.2968 0.0712
0.095 98.0 5000 0.3519 0.2927 0.0694

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.2
  • Datasets 1.18.2
  • Tokenizers 0.10.3