readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice_10_0
  model-index:
  - name: fine-tune-Wav2Vec2-XLS-R-300M-Indonesia
    results: []
  ---
  
  <!-- 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. -->
  
  # fine-tune-Wav2Vec2-XLS-R-300M-Indonesia
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_10_0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7924
  - Wer: 0.4307
  
  ## 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: 32
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 100
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.8421        | 6.33  | 500  | 0.7758          | 0.7386 |
  | 0.1875        | 12.66 | 1000 | 0.6039          | 0.5712 |
  | 0.1138        | 18.99 | 1500 | 0.6463          | 0.5170 |
  | 0.0774        | 25.32 | 2000 | 0.6814          | 0.4914 |
  | 0.0655        | 31.65 | 2500 | 0.7010          | 0.4778 |
  | 0.0536        | 37.97 | 3000 | 0.7267          | 0.4761 |
  | 0.0471        | 44.3  | 3500 | 0.7552          | 0.4693 |
  | 0.0402        | 50.63 | 4000 | 0.7474          | 0.4612 |
  | 0.0366        | 56.96 | 4500 | 0.7705          | 0.4560 |
  | 0.0324        | 63.29 | 5000 | 0.7253          | 0.4472 |
  | 0.0293        | 69.62 | 5500 | 0.7660          | 0.4441 |
  | 0.0254        | 75.95 | 6000 | 0.7816          | 0.4398 |
  | 0.0226        | 82.28 | 6500 | 0.7988          | 0.4378 |
  | 0.0202        | 88.61 | 7000 | 0.8009          | 0.4305 |
  | 0.0185        | 94.94 | 7500 | 0.7924          | 0.4307 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.10.0+cu113
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  