readme: ---
  language: mn
  license: apache-2.0
  tags:
  - whisper-event
  - hf-asr-leaderboard
  - generated_from_multiple_datasets
  datasets:
  - mozilla-foundation/common_voice_11_0
  - google/fleurs
  - bayartsogt/ulaanbal-v0
  - bayartsogt/youtube-mongolian-v1
  metrics:
  - wer
  - cer
  model-index:
  - name: whisper-large-v2-mn-13
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: mn
        split: test
      metrics:
      - type: wer
        value: 20.02403320952589
        name: Wer
      - type: cer
        value: 6.601024224251205
        name: Cer
  ---
  
  <!-- 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-large-v2-mn-13
  
  This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1689
  - Wer: 20.0240
  - Cer: 6.6010
  
  ## 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: 8
  - eval_batch_size: 4
  - 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: 25000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Cer     | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:-------:|:---------------:|:-------:|
  | 0.3921        | 0.09  | 1000  | 15.7845 | 0.4101          | 46.9030 |
  | 0.3115        | 0.17  | 2000  | 14.2911 | 0.3353          | 41.8451 |
  | 0.2659        | 0.26  | 3000  | 11.8131 | 0.2800          | 34.6406 |
  | 0.2477        | 0.35  | 4000  | 10.6659 | 0.2578          | 32.0024 |
  | 0.2274        | 0.43  | 5000  | 10.0460 | 0.2463          | 30.3419 |
  | 0.2059        | 0.52  | 6000  | 9.9264  | 0.2305          | 28.5558 |
  | 0.2092        | 0.61  | 7000  | 9.4277  | 0.2196          | 27.8785 |
  | 0.1956        | 0.69  | 8000  | 9.2745  | 0.2093          | 26.8353 |
  | 0.195         | 0.78  | 9000  | 8.9485  | 0.2042          | 26.6168 |
  | 0.195         | 0.87  | 10000 | 8.5324  | 0.2001          | 25.6718 |
  | 0.1795        | 0.95  | 11000 | 8.1786  | 0.1936          | 24.1698 |
  | 0.1575        | 1.04  | 12000 | 7.8653  | 0.1915          | 23.8912 |
  | 0.1358        | 1.13  | 13000 | 7.6749  | 0.1918          | 23.3778 |
  | 0.1509        | 1.21  | 14000 | 7.7221  | 0.1852          | 23.1811 |
  | 0.1474        | 1.3   | 15000 | 7.3246  | 0.1764          | 22.4984 |
  | 0.1461        | 1.39  | 16000 | 7.3187  | 0.1793          | 22.4110 |
  | 0.134         | 1.47  | 17000 | 7.1123  | 0.1737          | 21.9412 |
  | 0.1289        | 1.56  | 18000 | 7.4593  | 0.1727          | 22.0614 |
  | 0.1287        | 1.65  | 19000 | 7.0230  | 0.1701          | 21.4223 |
  | 0.1196        | 1.73  | 20000 | 6.9447  | 0.1666          | 21.2475 |
  | 0.1275        | 1.82  | 21000 | 6.7956  | 0.1653          | 20.8106 |
  | 0.1329        | 1.91  | 22000 | 6.7729  | 0.1622          | 20.3354 |
  | 0.1294        | 1.99  | 23000 | 6.6448  | 0.1606          | 20.2207 |
  | 0.1043        | 2.08  | 24000 | 6.6010  | 0.1689          | 20.0240 |
  | 0.079         | 2.17  | 25000 | 6.6246  | 0.1687          | 20.1005 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  