readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xlsr-53k-russian
    results: []
  ---
  
  <!-- 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-xlsr-53k-russian
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2660
  - Wer: 0.2052
  
  ## 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: 96
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 192
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 4.2873        | 1.09  | 400  | 0.8580          | 0.8982 |
  | 0.4728        | 2.19  | 800  | 0.3182          | 0.3892 |
  | 0.1639        | 9.83  | 1200 | 0.2374          | 0.2646 |
  | 0.1014        | 13.11 | 1600 | 0.2470          | 0.2467 |
  | 0.0754        | 16.39 | 2000 | 0.2516          | 0.2337 |
  | 0.0616        | 19.67 | 2400 | 0.2559          | 0.2237 |
  | 0.0505        | 22.95 | 2800 | 0.2557          | 0.2155 |
  | 0.0437        | 26.23 | 3200 | 0.2711          | 0.2099 |
  | 0.0377        | 29.51 | 3600 | 0.2660          | 0.2052 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  