readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice_10_0
  model-index:
  - name: fine-tune-Wav2Vec2-XLS-R-300M-Indonesia-3
    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-3
  
  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: 0.2856
  - Wer: 0.1931
  
  ## 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: 36
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 72
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 60
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.8503        | 4.0   | 460  | 1.2215          | 0.8013 |
  | 0.2917        | 8.0   | 920  | 0.2824          | 0.3055 |
  | 0.1487        | 12.0  | 1380 | 0.2719          | 0.2593 |
  | 0.0904        | 16.0  | 1840 | 0.2536          | 0.2448 |
  | 0.0741        | 20.0  | 2300 | 0.2620          | 0.2325 |
  | 0.0635        | 24.0  | 2760 | 0.2953          | 0.2354 |
  | 0.0541        | 28.0  | 3220 | 0.2683          | 0.2184 |
  | 0.048         | 32.0  | 3680 | 0.2707          | 0.2097 |
  | 0.0435        | 36.0  | 4140 | 0.2764          | 0.2111 |
  | 0.0377        | 40.0  | 4600 | 0.2874          | 0.2048 |
  | 0.0352        | 44.0  | 5060 | 0.2758          | 0.1999 |
  | 0.0304        | 48.0  | 5520 | 0.2808          | 0.1969 |
  | 0.0285        | 52.0  | 5980 | 0.2860          | 0.1943 |
  | 0.0258        | 56.0  | 6440 | 0.2867          | 0.1943 |
  | 0.0239        | 60.0  | 6900 | 0.2856          | 0.1931 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.10.0+cu113
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  