readme: ---
  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
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # wav2vec2-large-xls-r-300m-sakha
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/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
  