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
  metrics:
  - wer
  - cer
  model-index:
  - name: whisper-small-mn-11
    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: 51.96635350666375
        name: Wer
      - type: cer
        value: 19.87703213138759
        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-11
  
  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: 1.0138
  - Wer: 51.9664
  - Cer: 19.8770
  
  ## 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     |
  |:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:|
  | 0.0025        | 32.26  | 1000  | 0.8913          | 53.6214 | 20.6866 |
  | 0.0007        | 64.52  | 2000  | 0.9326          | 52.1685 | 19.5991 |
  | 0.0001        | 96.77  | 3000  | 1.0138          | 51.9664 | 19.8770 |
  | 0.0001        | 129.03 | 4000  | 1.0639          | 52.1248 | 19.9178 |
  | 0.0           | 161.29 | 5000  | 1.1236          | 52.0428 | 19.9652 |
  | 0.0           | 193.55 | 6000  | 1.1677          | 52.4634 | 20.0351 |
  | 0.0           | 225.81 | 7000  | 1.2224          | 52.5836 | 20.1258 |
  | 0.0           | 258.06 | 8000  | 1.2633          | 52.7310 | 20.2073 |
  | 0.0           | 290.32 | 9000  | 1.3152          | 52.8184 | 20.2273 |
  | 0.0           | 322.58 | 10000 | 1.3530          | 52.9495 | 20.3080 |
  | 0.0           | 354.84 | 11000 | 1.3995          | 53.0260 | 20.3088 |
  | 0.0           | 387.1  | 12000 | 1.4306          | 52.9878 | 20.2057 |
  | 0.0           | 419.35 | 13000 | 1.4674          | 52.9714 | 20.3113 |
  | 0.0           | 451.61 | 14000 | 1.4859          | 52.9386 | 20.2947 |
  | 0.0           | 483.87 | 15000 | 1.4994          | 52.9768 | 20.3280 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  