readme: ---
  license: apache-2.0
  tags:
  - whisper-event
  - hf-asr-leaderboard
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  - google/fleurs
  metrics:
  - wer
  model-index:
    - name: whisper-medium-mn-4-bayartsogt
      results:
        - task:
            name: Automatic Speech Recognition
            type: automatic-speech-recognition
          dataset:
            name: Common Voice 11.0
            type: mozilla-foundation/common_voice_11_0
            config: mn
            split: test
            args:
              language: mn
          metrics:
            - name: Wer
              type: wer
              value: 33.029276818876994
  ---
  
  <!-- 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-medium-mn-4
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6015
  - Wer: 33.0293
  - Cer: 10.9236
  
  ## 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: 32
  - eval_batch_size: 16
  - 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: 15000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     | Cer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
  | 0.0362        | 4.26  | 1000  | 0.4204          | 40.2720 | 13.8389 |
  | 0.0087        | 8.51  | 2000  | 0.4712          | 37.4918 | 12.9175 |
  | 0.0044        | 12.77 | 3000  | 0.4893          | 36.3393 | 12.4727 |
  | 0.0033        | 17.02 | 4000  | 0.5159          | 35.8423 | 12.2933 |
  | 0.0017        | 21.28 | 5000  | 0.5183          | 35.2797 | 12.1104 |
  | 0.0016        | 25.53 | 6000  | 0.5422          | 35.4326 | 11.7454 |
  | 0.0011        | 29.79 | 7000  | 0.5361          | 34.5314 | 11.5196 |
  | 0.0004        | 34.04 | 8000  | 0.5406          | 34.0998 | 11.3650 |
  | 0.0006        | 38.3  | 9000  | 0.5540          | 33.8650 | 11.2912 |
  | 0.0002        | 42.55 | 10000 | 0.5748          | 34.0889 | 11.5333 |
  | 0.0003        | 46.81 | 11000 | 0.5771          | 34.5641 | 11.4895 |
  | 0.0           | 51.06 | 12000 | 0.5809          | 33.4335 | 11.2070 |
  | 0.0           | 55.32 | 13000 | 0.5941          | 33.2095 | 11.0009 |
  | 0.0           | 59.57 | 14000 | 0.6015          | 33.0293 | 10.9236 |
  | 0.0           | 63.83 | 15000 | 0.6045          | 33.0347 | 10.9125 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  