readme: ---
  language:
  - sr
  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 Serbian El Greco
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0,google/fleurs sr,sr_rs
        type: mozilla-foundation/common_voice_11_0,google/fleurs
        config: sr
        split: None
      metrics:
      - name: Wer
        type: wer
        value: 12.140833670578713
  ---
  
  <!-- 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 Serbian 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 sr,sr_rs dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4868
  - Wer: 12.1408
  
  ## 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     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.0222        | 2.72  | 1000  | 0.3442          | 14.0834 |
  | 0.0032        | 5.43  | 2000  | 0.4106          | 14.5285 |
  | 0.0011        | 8.15  | 3000  | 0.4331          | 12.8693 |
  | 0.0029        | 10.87 | 4000  | 0.3948          | 12.6265 |
  | 0.0012        | 13.59 | 5000  | 0.4512          | 12.6669 |
  | 0.0009        | 16.3  | 6000  | 0.4890          | 12.7479 |
  | 0.001         | 19.02 | 7000  | 0.4868          | 12.1408 |
  | 0.0016        | 21.74 | 8000  | 0.4780          | 12.7074 |
  | 0.0002        | 24.46 | 9000  | 0.4902          | 12.2218 |
  | 0.0012        | 27.17 | 10000 | 0.5059          | 12.6669 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 2.0.0.dev20221216+cu116
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  