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-small-mn-12
    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: 32.33012890539655
        name: Wer
      - type: cer
        value: 13.34925204253124
        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-small-mn-12
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2949
  - Wer: 32.3301
  - Cer: 13.3493
  
  ## 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: 32
  - 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  | Validation Loss | Wer     | Cer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
  | 0.3012        | 1.05  | 1000  | 0.3749          | 43.2379 | 17.6739 |
  | 0.2171        | 2.11  | 2000  | 0.3012          | 36.7435 | 15.2029 |
  | 0.1732        | 3.16  | 3000  | 0.2823          | 33.4225 | 13.7561 |
  | 0.145         | 4.21  | 4000  | 0.2822          | 32.4995 | 13.2436 |
  | 0.1159        | 5.27  | 5000  | 0.2949          | 32.3301 | 13.3493 |
  | 0.0863        | 6.32  | 6000  | 0.3116          | 32.7234 | 13.3892 |
  | 0.0685        | 7.38  | 7000  | 0.3343          | 32.4776 | 13.3077 |
  | 0.0506        | 8.43  | 8000  | 0.3584          | 33.3952 | 13.7736 |
  | 0.0336        | 9.48  | 9000  | 0.3861          | 33.7011 | 13.8493 |
  | 0.0215        | 10.54 | 10000 | 0.4193          | 33.7011 | 14.0140 |
  | 0.0141        | 11.59 | 11000 | 0.4463          | 34.0343 | 14.0298 |
  | 0.0089        | 12.64 | 12000 | 0.4660          | 33.6137 | 13.8052 |
  | 0.0057        | 13.7  | 13000 | 0.4913          | 33.9797 | 13.9849 |
  | 0.0039        | 14.75 | 14000 | 0.5078          | 33.9906 | 14.0656 |
  | 0.0033        | 15.81 | 15000 | 0.5244          | 33.7721 | 13.9192 |
  | 0.0024        | 16.86 | 16000 | 0.5358          | 33.7612 | 13.7910 |
  | 0.0018        | 17.91 | 17000 | 0.5469          | 33.6465 | 13.8468 |
  | 0.0013        | 18.97 | 18000 | 0.5614          | 33.6683 | 13.7553 |
  | 0.0014        | 20.02 | 19000 | 0.5707          | 33.6574 | 13.8884 |
  | 0.0006        | 21.07 | 20000 | 0.5835          | 34.0671 | 14.0764 |
  | 0.0007        | 22.13 | 21000 | 0.5927          | 33.9742 | 14.0772 |
  | 0.0005        | 23.18 | 22000 | 0.5994          | 34.0398 | 14.0290 |
  | 0.0004        | 24.24 | 23000 | 0.6067          | 33.9469 | 13.9217 |
  | 0.0003        | 25.29 | 24000 | 0.6109          | 33.9688 | 13.9591 |
  | 0.0003        | 26.34 | 25000 | 0.6130          | 33.8267 | 13.8360 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  