readme: ---
  language:
  - hu
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  - google/fleurs
  metrics:
  - wer
  model-index:
  - name: Whisper medium Hungarian El Greco
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0
        type: mozilla-foundation/common_voice_11_0
        config: hu
        split: test
      metrics:
      - name: Wer
        type: wer
        value: 18.642158316039133
  ---
  
  <!-- 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 medium Hungarian El Greco
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0,google/fleurs hu,hu_hu dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3428
  - Wer: 18.6422
  
  ## 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: 3e-06
  - train_batch_size: 32
  - eval_batch_size: 16
  - seed: 42
  - distributed_type: multi-GPU
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 10000
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.0621        | 1.05  | 1000  | 0.2690          | 20.5099 |
  | 0.0174        | 2.1   | 2000  | 0.2705          | 19.2292 |
  | 0.006         | 3.15  | 3000  | 0.2954          | 18.9890 |
  | 0.0028        | 4.2   | 4000  | 0.3093          | 18.8023 |
  | 0.0016        | 5.25  | 5000  | 0.3240          | 18.9653 |
  | 0.0018        | 6.3   | 6000  | 0.3313          | 18.6451 |
  | 0.0014        | 7.35  | 7000  | 0.3330          | 18.9446 |
  | 0.0016        | 8.39  | 8000  | 0.3428          | 18.6422 |
  | 0.0015        | 9.44  | 9000  | 0.3508          | 18.9564 |
  | 0.001         | 10.49 | 10000 | 0.3569          | 18.8556 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 2.0.0.dev20221216+cu116
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  