readme: ---
  language:
  - bg
  license: apache-2.0
  tags:
  - hf-asr-leaderboard
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Bg - Yonchevisky_tes2t
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: bg
        split: test
        args: 'config: bg, split: test'
      metrics:
      - name: Wer
        type: wer
        value: 61.83524504692388
  ---
  
  <!-- 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 Bg - Yonchevisky_tes2t
  
  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7377
  - Wer: 61.8352
  
  ## 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: 2
  - eval_batch_size: 2
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 1000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer      |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.8067        | 0.37  | 100  | 1.6916          | 137.6897 |
  | 0.9737        | 0.73  | 200  | 1.1197          | 78.3571  |
  | 0.7747        | 1.1   | 300  | 0.9763          | 73.8906  |
  | 0.6672        | 1.47  | 400  | 0.8972          | 70.7102  |
  | 0.6196        | 1.84  | 500  | 0.8329          | 67.4545  |
  | 0.4849        | 2.21  | 600  | 0.7968          | 66.6029  |
  | 0.4402        | 2.57  | 700  | 0.7597          | 62.7795  |
  | 0.4601        | 2.94  | 800  | 0.7385          | 61.8642  |
  | 0.3545        | 3.31  | 900  | 0.7394          | 61.5050  |
  | 0.3596        | 3.68  | 1000 | 0.7377          | 61.8352  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  