readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - filipino_voice
  model-index:
  - name: english-filipino-wav2vec2-l-xls-r-test
    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. -->
  
  # english-filipino-wav2vec2-l-xls-r-test
  
  This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english) on the filipino_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5795
  - Wer: 0.3996
  
  ## 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: 0.001
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.0751        | 2.09  | 400  | 2.4744          | 0.9804 |
  | 0.7852        | 4.19  | 800  | 0.5836          | 0.5620 |
  | 0.3751        | 6.28  | 1200 | 0.4873          | 0.4658 |
  | 0.2578        | 8.38  | 1600 | 0.5725          | 0.5289 |
  | 0.1897        | 10.47 | 2000 | 0.5342          | 0.4856 |
  | 0.1394        | 12.57 | 2400 | 0.5677          | 0.4761 |
  | 0.1048        | 14.66 | 2800 | 0.5708          | 0.4415 |
  | 0.0848        | 16.75 | 3200 | 0.5908          | 0.4374 |
  | 0.0652        | 18.85 | 3600 | 0.5795          | 0.3996 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  