readme: ---
  license: apache-2.0
  tags:
  - whisper-event
  - hf-asr-leaderboard
  - generated_from_trainer
  datasets:
  - bayartsogt/youtube-mongolian-v1
  metrics:
  - wer
  model-index:
    - name: whisper-small-mn-6-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: 35.8859514966135
  ---
  
  <!-- 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-6
  
  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: 0.3296
  - Wer: 35.8860
  - Cer: 13.3108
  
  ## 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     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
  | 0.3774        | 0.8   | 1000  | 0.4319          | 53.2773 | 19.6627 |
  | 0.2926        | 1.61  | 2000  | 0.3493          | 40.4960 | 15.0214 |
  | 0.2331        | 2.41  | 3000  | 0.3346          | 39.1741 | 14.7689 |
  | 0.1636        | 3.22  | 4000  | 0.3287          | 36.9237 | 13.7943 |
  | 0.1157        | 4.02  | 5000  | 0.3296          | 35.8860 | 13.3108 |
  | 0.1271        | 4.82  | 6000  | 0.3422          | 36.0717 | 13.5702 |
  | 0.0879        | 5.63  | 7000  | 0.3661          | 36.6943 | 13.7780 |
  | 0.0574        | 6.43  | 8000  | 0.3884          | 36.4595 | 13.5015 |
  | 0.036         | 7.23  | 9000  | 0.4128          | 37.1422 | 13.8424 |
  | 0.0229        | 8.04  | 10000 | 0.4321          | 36.8582 | 13.8475 |
  | 0.0241        | 8.84  | 11000 | 0.4530          | 37.1095 | 13.8673 |
  | 0.0123        | 9.65  | 12000 | 0.4763          | 37.5956 | 13.9583 |
  | 0.007         | 10.45 | 13000 | 0.4939          | 37.3116 | 13.9360 |
  | 0.0047        | 11.25 | 14000 | 0.5054          | 37.1750 | 13.8106 |
  | 0.0036        | 12.06 | 15000 | 0.5093          | 37.5082 | 13.8930 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  