readme: ---
  language:
  - id
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - hf-asr-leaderboard
  - robust-speech-event
  datasets:
  - mozilla-foundation/common_voice_8_0
  metrics:
  - wer
  - cer
  model-index:
  - name: wav2vec2-large-xls-r-1b-Indonesian
    results:
    - task:
        type: automatic-speech-recognition
        name: Speech Recognition
      dataset:
        type: mozilla-foundation/common_voice_8_0
        name: Common Voice id
        args: id
      metrics:
      - type: wer
        value: 45.51
        name: Test WER
      - type: cer
        value: 16.43
        name: Test CER
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: id
      metrics:
      - name: Test WER
        type: wer
        value: 72.73
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: id
      metrics:
      - name: Test WER
        type: wer
        value: 79.29
  ---
  
  <!-- 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. -->
  
  # wav2vec2-large-xls-r-1b-Indonesian
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9550
  - Wer: 0.4551
  - Cer: 0.1643
  
  
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 0.0003
  - train_batch_size: 64
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 400
  - num_epochs: 50
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
  | 3.663         | 7.69  | 200  | 0.7898          | 0.6039 | 0.1848 |
  | 0.7424        | 15.38 | 400  | 1.0215          | 0.5615 | 0.1924 |
  | 0.4494        | 23.08 | 600  | 1.0901          | 0.5249 | 0.1932 |
  | 0.5075        | 30.77 | 800  | 1.1013          | 0.5079 | 0.1935 |
  | 0.4671        | 38.46 | 1000 | 1.1034          | 0.4916 | 0.1827 |
  | 0.1928        | 46.15 | 1200 | 0.9550          | 0.4551 | 0.1643 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  