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metadata
language:
  - cy
license: apache-2.0
tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  - cy
  - robust-speech-event
  - model_for_talk
datasets:
  - common_voice
model-index:
  - name: XLS-R-300M - Welsh
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 7
          type: mozilla-foundation/common_voice_7_0
          args: cy
        metrics:
          - name: Test WER
            type: wer
            value: 31.003
          - name: Test CER
            type: cer
            value: 7.775

wav2vec2-large-xls-r-300m-welsh

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - CY dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2650
  • Wer: 0.2702

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: 7e-05
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 3000
  • num_epochs: 50.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.3454 8.2 3000 0.4926 0.5703
1.1202 16.39 6000 0.3529 0.3944
1.0058 24.59 9000 0.3143 0.3341
0.9287 32.79 12000 0.2896 0.2980
0.8849 40.98 15000 0.2727 0.2798
0.8665 49.18 18000 0.2662 0.2696

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.1+cu102
  • Datasets 1.18.3
  • Tokenizers 0.11.0