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
  metrics:
  - wer
  model-index:
    - name: whisper-small-mn-3-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: 30.36923749180686
  ---
  
  <!-- 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-3
  
  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: 0.3277
  - Wer: 30.3692
  - Cer: 10.9030
  
  ## 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     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
  | 0.3408        | 0.61  | 1000  | 0.4062          | 47.6841 | 17.3811 |
  | 0.2261        | 1.22  | 2000  | 0.3262          | 37.8086 | 13.6466 |
  | 0.2135        | 1.83  | 3000  | 0.2863          | 33.7175 | 12.2246 |
  | 0.1643        | 2.43  | 4000  | 0.2803          | 32.5978 | 11.4526 |
  | 0.1198        | 3.04  | 5000  | 0.2747          | 31.1121 | 11.0533 |
  | 0.1279        | 3.65  | 6000  | 0.2757          | 30.7243 | 10.8927 |
  | 0.0891        | 4.26  | 7000  | 0.2878          | 30.9209 | 11.0610 |
  | 0.0899        | 4.87  | 8000  | 0.2906          | 30.6642 | 11.0799 |
  | 0.0648        | 5.48  | 9000  | 0.3054          | 30.5986 | 10.9030 |
  | 0.0436        | 6.09  | 10000 | 0.3184          | 30.5222 | 10.9434 |
  | 0.0468        | 6.7   | 11000 | 0.3277          | 30.3692 | 10.9030 |
  | 0.0291        | 7.3   | 12000 | 0.3411          | 30.9810 | 11.1572 |
  | 0.0275        | 7.91  | 13000 | 0.3476          | 31.0684 | 11.1555 |
  | 0.0196        | 8.52  | 14000 | 0.3572          | 30.9154 | 11.1065 |
  | 0.0159        | 9.13  | 15000 | 0.3600          | 31.0356 | 11.2087 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  