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-small-mn-2-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: 40.87830456630981
  ---
  
  <!-- 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-2
  
  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: 0.7259
  - Wer: 40.8783
  - Cer: 13.9617
  
  ## 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     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
  | 0.0839        | 4.26  | 1000  | 0.4647          | 45.7286 | 16.0020 |
  | 0.0093        | 8.51  | 2000  | 0.5434          | 43.9753 | 15.2446 |
  | 0.0044        | 12.77 | 3000  | 0.6009          | 43.6257 | 15.1717 |
  | 0.0029        | 17.02 | 4000  | 0.6166          | 43.0031 | 14.7578 |
  | 0.002         | 21.28 | 5000  | 0.6390          | 42.6098 | 14.7286 |
  | 0.001         | 25.53 | 6000  | 0.6558          | 41.7468 | 14.3516 |
  | 0.0021        | 29.79 | 7000  | 0.6714          | 42.3039 | 14.4589 |
  | 0.0003        | 34.04 | 8000  | 0.6791          | 41.0586 | 13.9506 |
  | 0.0001        | 38.3  | 9000  | 0.6949          | 41.3808 | 14.1670 |
  | 0.0013        | 42.55 | 10000 | 0.6875          | 41.4682 | 14.2983 |
  | 0.0001        | 46.81 | 11000 | 0.6937          | 40.9165 | 13.9549 |
  | 0.0001        | 51.06 | 12000 | 0.7092          | 40.9275 | 13.9549 |
  | 0.0           | 55.32 | 13000 | 0.7190          | 40.9657 | 13.9703 |
  | 0.0           | 59.57 | 14000 | 0.7259          | 40.8783 | 13.9617 |
  | 0.0           | 63.83 | 15000 | 0.7292          | 40.8838 | 13.9274 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  