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metadata
language:
  - cv
license: apache-2.0
tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  - cv
  - robust-speech-event
  - model_for_talk
  - hf-asr-leaderboard
datasets:
  - mozilla-foundation/common_voice_7_0
model-index:
  - name: XLS-R-300M - Chuvash
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 7
          type: mozilla-foundation/common_voice_7_0
          args: cv
        metrics:
          - name: Test WER
            type: wer
            value: 60.31
          - name: Test CER
            type: cer
            value: 15.08

wav2vec2-large-xls-r-300m-chuvash

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

  • Loss: 0.7651
  • Wer: 0.6166

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 100.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.8032 8.77 500 0.8059 0.8352
1.2608 17.54 1000 0.5828 0.6769
1.1337 26.32 1500 0.6892 0.6908
1.0457 35.09 2000 0.7077 0.6781
0.97 43.86 2500 0.5993 0.6228
0.8767 52.63 3000 0.7213 0.6604
0.8223 61.4 3500 0.8161 0.6968
0.7441 70.18 4000 0.7057 0.6184
0.7011 78.95 4500 0.7027 0.6024
0.6542 87.72 5000 0.7092 0.5979
0.6081 96.49 5500 0.7917 0.6324

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.1+cu102
  • Datasets 1.17.1.dev0
  • Tokenizers 0.11.0