readme: ---
  license: apache-2.0
  tags:
    - whisper-event
    - hf-asr-leaderboard
    - generated_from_trainer
  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-8-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: 26.518461874590344
            - name: Cer
              type: cer
              value: 9.46811616603981
  ---
  
  <!-- 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-8
  
  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: 0.2421
  - Wer: 26.5185
  - Cer: 9.4681
  
  ## 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: 15000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     | Cer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
  | 0.3717        | 0.35  | 1000  | 0.4004          | 46.9576 | 16.9664 |
  | 0.286         | 0.69  | 2000  | 0.3129          | 37.3935 | 13.5504 |
  | 0.2287        | 1.04  | 3000  | 0.2768          | 33.1931 | 11.7806 |
  | 0.2257        | 1.39  | 4000  | 0.2590          | 30.7243 | 11.0232 |
  | 0.2029        | 1.73  | 5000  | 0.2428          | 29.2003 | 10.4144 |
  | 0.1691        | 2.08  | 6000  | 0.2408          | 28.4357 | 10.0306 |
  | 0.1626        | 2.43  | 7000  | 0.2369          | 28.0588 | 10.0486 |
  | 0.1588        | 2.77  | 8000  | 0.2321          | 27.2340 | 9.6819  |
  | 0.1271        | 3.12  | 9000  | 0.2349          | 26.8407 | 9.5574  |
  | 0.1263        | 3.47  | 10000 | 0.2356          | 27.1630 | 9.6519  |
  | 0.1314        | 3.81  | 11000 | 0.2340          | 26.5567 | 9.4278  |
  | 0.1062        | 4.16  | 12000 | 0.2390          | 26.6332 | 9.5162  |
  | 0.1081        | 4.5   | 13000 | 0.2398          | 26.5840 | 9.5085  |
  | 0.1033        | 4.85  | 14000 | 0.2402          | 26.7096 | 9.4801  |
  | 0.097         | 5.2   | 15000 | 0.2421          | 26.5185 | 9.4681  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  