readme: ---
  license: apache-2.0
  language:
  - ru
  tags:
  - generated_from_trainer
  - hf-asr-leaderboard
  - robust-speech-event
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-xls-r-300m-Russian-small
    results:
    - task:
        name: Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice ru
        type: common_voice
        args: ru
      metrics:
      - name: Test WER
        type: wer
        value: 48.38
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: ru
      metrics:
      - name: Test WER
        type: wer
        value: 58.25
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: ru
      metrics:
      - name: Test WER
        type: wer
        value: 56.83
  ---
  
  <!-- 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-xls-r-300m-Russian-small
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3514
  - Wer: 0.4838
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 5.512         | 1.32  | 400  | 3.2207          | 1.0    |
  | 3.1562        | 2.65  | 800  | 3.0166          | 1.0    |
  | 1.5211        | 3.97  | 1200 | 0.7134          | 0.8275 |
  | 0.6724        | 5.3   | 1600 | 0.4713          | 0.6402 |
  | 0.4693        | 6.62  | 2000 | 0.3904          | 0.5668 |
  | 0.3693        | 7.95  | 2400 | 0.3609          | 0.5121 |
  | 0.3004        | 9.27  | 2800 | 0.3514          | 0.4838 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 1.14.0
  - Tokenizers 0.10.3
  