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metadata
language:
  - sah
license: apache-2.0
tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  - sah
  - robust-speech-event
  - model_for_talk
  - hf-asr-leaderboard
datasets:
  - mozilla-foundation/common_voice_7_0
model-index:
  - name: XLS-R-300M - Sakha
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 7
          type: mozilla-foundation/common_voice_7_0
          args: sah
        metrics:
          - name: Test WER
            type: wer
            value: 44.196
          - name: Test CER
            type: cer
            value: 10.271

wav2vec2-large-xls-r-300m-sakha

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

  • Loss: 0.4995
  • Wer: 0.4421

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: 1
  • 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
1.8597 8.47 500 0.7731 0.7211
1.2508 16.95 1000 0.5368 0.5989
1.1066 25.42 1500 0.5034 0.5533
1.0064 33.9 2000 0.4686 0.5114
0.9324 42.37 2500 0.4927 0.5056
0.876 50.85 3000 0.4734 0.4795
0.8082 59.32 3500 0.4748 0.4799
0.7604 67.8 4000 0.4949 0.4691
0.7241 76.27 4500 0.5090 0.4627
0.6739 84.75 5000 0.4967 0.4452
0.6447 93.22 5500 0.5071 0.4437

Framework versions

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