readme: ---
  language:
  - ko
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - fleurs
  metrics:
  - wer
  model-index:
  - name: Whisper Small Ko(FLUERS) - by p4b
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: google/fleurs ko_kr
        type: google/fleurs
        config: ko_kr
        split: test
      metrics:
      - name: Wer
        type: wer
        value: 20.251271313191744
  ---
  
  <!-- 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 Ko(FLUERS) - by p4b
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the FLUERS Korean dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2893
  - Wer: 19.2
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  ### Dataset filtering
  
  Some of datas from FLUERS are not used for training and evaluation.
  Most of filtered datas are not fit to model or including non-korean symbols.
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 5e-07
  - train_batch_size: 96
  - eval_batch_size: 64
  - 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      |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.3016        | 32.0  | 800  | 0.4048          | 140.4726 |
  | 0.0451        | 64.0  | 1600 | 0.2893          | 19.2043  |
  | 0.0169        | 96.0  | 2400 | 0.3110          | 20.2513  |
  | 0.0092        | 128.0 | 3200 | 0.3240          | 20.0419  |
  | 0.0062        | 160.0 | 4000 | 0.3335          | 20.0419  |
  | 0.0045        | 192.0 | 4800 | 0.3416          | 20.0718  |
  | 0.0035        | 224.0 | 5600 | 0.3501          | 20.1615  |
  | 0.0028        | 256.0 | 6400 | 0.3562          | 20.3709  |
  | 0.0024        | 288.0 | 7200 | 0.3618          | 20.0120  |
  | 0.002         | 320.0 | 8000 | 0.3669          | 20.1017  |
  | 0.0017        | 352.0 | 8800 | 0.3704          | 20.1914  |
  | 0.0017        | 384.0 | 9600 | 0.3723          | 20.2513  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.14.0.dev20221208+cu116
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  