readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  metrics:
  - wer
  model-index:
  - name: w2v2-xlsr-indonesian
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: common_voice
        type: common_voice
        config: id
        split: train+validation
        args: id
      metrics:
      - name: Wer
        type: wer
        value: 0.211635278761887
  ---
  
  <!-- 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. -->
  
  # w2v2-xlsr-indonesian
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2496
  - Wer: 0.2116
  
  ## 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: 0.0001
  - train_batch_size: 64
  - eval_batch_size: 32
  - 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: 300
  - num_epochs: 60.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 9.828         | 3.23  | 100  | 3.3112          | 1.0    |
  | 2.99          | 6.45  | 200  | 2.8944          | 1.0    |
  | 2.8597        | 9.68  | 300  | 2.8430          | 1.0    |
  | 2.6267        | 12.9  | 400  | 1.6697          | 0.9975 |
  | 1.3279        | 16.13 | 500  | 0.5147          | 0.5183 |
  | 0.8697        | 19.35 | 600  | 0.3648          | 0.3825 |
  | 0.7173        | 22.58 | 700  | 0.3172          | 0.3332 |
  | 0.6268        | 25.81 | 800  | 0.3027          | 0.2900 |
  | 0.5733        | 29.03 | 900  | 0.2921          | 0.2710 |
  | 0.5283        | 32.26 | 1000 | 0.2731          | 0.2546 |
  | 0.4865        | 35.48 | 1100 | 0.2690          | 0.2397 |
  | 0.4559        | 38.71 | 1200 | 0.2581          | 0.2330 |
  | 0.4352        | 41.94 | 1300 | 0.2620          | 0.2254 |
  | 0.4265        | 45.16 | 1400 | 0.2496          | 0.2228 |
  | 0.3987        | 48.39 | 1500 | 0.2571          | 0.2219 |
  | 0.3977        | 51.61 | 1600 | 0.2514          | 0.2138 |
  | 0.3786        | 54.84 | 1700 | 0.2533          | 0.2142 |
  | 0.3763        | 58.06 | 1800 | 0.2496          | 0.2116 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  