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wav2vec2-large-xls-r-300m-Arabic

Automatic Speech Recognition
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PyTorch
wav2vec2
Generated from Trainer
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wav2vec2-large-xls-r-300m-Arabic / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: wav2vec2-large-xls-r-300m-Arabic-colab
    results: []

wav2vec2-large-xls-r-300m-Arabic-colab

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

  • Loss: 0.0001
  • Wer: 0.0703
  • Cer: 0.0310

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: 16
  • eval_batch_size: 6
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 250
  • num_epochs: 30.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.1001 1.0 51 0.0159 0.0647 0.0295
0.0576 2.0 102 0.0109 0.0819 0.0408
0.0598 3.0 153 0.0096 0.1153 0.0541
0.0636 4.0 204 0.0099 0.0594 0.0239
0.0642 5.0 255 0.0107 0.1043 0.0447
0.0551 6.0 306 0.0106 0.0575 0.0208
0.0543 7.0 357 0.0078 0.0157 0.0042
0.0516 8.0 408 0.0068 0.1144 0.0533
0.0454 9.0 459 0.0054 0.1058 0.0547
0.0308 10.0 510 0.0041 0.0742 0.0364
0.0296 11.0 561 0.0042 0.1146 0.0540
0.0252 12.0 612 0.0028 0.0971 0.0453
0.0236 13.0 663 0.0026 0.0803 0.0359
0.0238 14.0 714 0.0023 0.0783 0.0334
0.0185 15.0 765 0.0023 0.0654 0.0272
0.0185 16.0 816 0.0023 0.0522 0.0182
0.0159 17.0 867 0.0012 0.0396 0.0130
0.0161 18.0 918 0.0020 0.0580 0.0216
0.0142 19.0 969 0.0010 0.0168 0.0037
0.0164 20.0 1020 0.0009 0.0511 0.0221
0.011 21.0 1071 0.0006 0.0192 0.0054
0.0087 22.0 1122 0.0004 0.0198 0.0058
0.0083 23.0 1173 0.0004 0.0251 0.0093
0.0085 24.0 1224 0.0004 0.0677 0.0314
0.0054 25.0 1275 0.0003 0.0587 0.0250
0.0057 26.0 1326 0.0002 0.0435 0.0172
0.007 27.0 1377 0.0005 0.0696 0.0305
0.007 28.0 1428 0.0003 0.0673 0.0294
0.0059 29.0 1479 0.0001 0.0688 0.0301
0.0045 30.0 1530 0.0001 0.0703 0.0310

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2