readme: ---
  language:
  - hu
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Hungarian - Robust
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 hu
        type: mozilla-foundation/common_voice_11_0
        config: hu
        split: test
        args: hu
      metrics:
      - type: wer
        value: 30.904239549362583
        name: Wer
      - type: wer
        value: 26.15
        name: WER
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: google/fleurs
        type: google/fleurs
        config: hu_hu
        split: test
      metrics:
      - type: wer
        value: 35.49
        name: WER
  ---
  
  <!-- 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 Hungarian - Robust
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 hu dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5243
  - Wer: 30.9042
  
  ## 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: 5e-05
  - train_batch_size: 128
  - eval_batch_size: 64
  - 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: 5000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.0763        | 7.46  | 500  | 0.5268          | 40.5099 |
  | 0.0147        | 14.93 | 1000 | 0.5233          | 36.1429 |
  | 0.0064        | 22.39 | 1500 | 0.5467          | 35.0934 |
  | 0.0045        | 29.85 | 2000 | 0.5434          | 34.2929 |
  | 0.0019        | 37.31 | 2500 | 0.5348          | 32.7868 |
  | 0.0008        | 44.78 | 3000 | 0.5314          | 32.0605 |
  | 0.0008        | 52.24 | 3500 | 0.5438          | 32.6920 |
  | 0.0005        | 59.7  | 4000 | 0.5428          | 32.0931 |
  | 0.0003        | 67.16 | 4500 | 0.5328          | 31.2511 |
  | 0.0004        | 74.63 | 5000 | 0.5292          | 31.1236 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  