readme: ---
  language:
  - ba
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Bashkir
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 ba
        type: mozilla-foundation/common_voice_11_0
        config: ba
        split: test
        args: ba
      metrics:
      - name: Wer
        type: wer
        value: 15.072300680807968
  ---
  
  <!-- 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. -->
  
  # Whisper Small Bashkir
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 ba dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2589
  - Wer: 15.0723
  
  ## 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: 1e-05
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 30000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.1637        | 1.01  | 2000  | 0.2555          | 26.4682 |
  | 0.1375        | 2.01  | 4000  | 0.2223          | 21.5394 |
  | 0.0851        | 3.02  | 6000  | 0.2086          | 19.6725 |
  | 0.0573        | 4.02  | 8000  | 0.2178          | 18.4280 |
  | 0.036         | 5.03  | 10000 | 0.2312          | 17.8248 |
  | 0.0238        | 6.04  | 12000 | 0.2621          | 17.4096 |
  | 0.0733        | 7.04  | 14000 | 0.2120          | 16.5656 |
  | 0.0111        | 8.05  | 16000 | 0.2682          | 16.2291 |
  | 0.0155        | 9.05  | 18000 | 0.2677          | 15.9242 |
  | 0.0041        | 10.06 | 20000 | 0.3178          | 15.9534 |
  | 0.0023        | 12.01 | 22000 | 0.3218          | 16.0536 |
  | 0.0621        | 13.01 | 24000 | 0.2313          | 15.6169 |
  | 0.0022        | 14.02 | 26000 | 0.2887          | 15.1083 |
  | 0.0199        | 15.02 | 28000 | 0.2553          | 15.1848 |
  | 0.0083        | 16.03 | 30000 | 0.2589          | 15.0723 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  