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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
model-index:
  - name: xls-r-fleurs_zu-run1
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: audiofolder
          type: audiofolder
          config: default
          split: validation
          args: default
        metrics:
          - name: Wer
            type: wer
            value: 0.600381

xls-r-fleurs_zu-run1

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the FLEURS (zu) dataset. It achieves the following results:

  • Wer (Validation): 61.41%
  • Wer (Test): 60.23%

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0003
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 3
  • total_train_batch_size: 12
  • 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 (Train)
50 19.607200 9.162900 1.000000
100 7.038300 4.738822 1.000000
150 4.190100 3.359574 1.000000
200 3.161900 3.032595 1.000000
250 3.004700 2.994741 1.000000
300 2.988300 2.955285 1.000000
350 2.675800 1.816109 1.000000
400 1.064400 0.866473 0.814220
450 0.601600 0.696754 0.712340
500 0.506900 0.662974 0.716426
550 0.432200 0.598446 0.667121
600 0.358700 0.618853 0.681013
650 0.333300 0.564290 0.627349
700 0.283100 0.573746 0.646418
750 0.250800 0.577737 0.639608
800 0.232200 0.557288 0.604467
850 0.191200 0.538959 0.590030
900 0.195600 0.549700 0.600654
950 0.193000 0.579098 0.611278
1000 0.169900 0.578752 0.600381

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3