readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - filipino_voice
  model-index:
  - name: english-filipino-wav2vec2-l-xls-r-test-04
    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-04
  
  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: 1.0713
  - Wer: 0.5078
  
  ## 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: 0.002
  - 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: 40
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.2131        | 2.09  | 400  | 0.7100          | 0.6832 |
  | 0.6539        | 4.19  | 800  | 0.8307          | 0.6602 |
  | 0.5081        | 6.28  | 1200 | 0.7120          | 0.6297 |
  | 0.42          | 8.38  | 1600 | 0.7309          | 0.6299 |
  | 0.3482        | 10.47 | 2000 | 0.7665          | 0.6148 |
  | 0.293         | 12.57 | 2400 | 0.7091          | 0.5840 |
  | 0.265         | 14.66 | 2800 | 0.8170          | 0.6102 |
  | 0.2294        | 16.75 | 3200 | 0.9715          | 0.6216 |
  | 0.1872        | 18.85 | 3600 | 0.8516          | 0.5837 |
  | 0.1644        | 20.94 | 4000 | 0.8408          | 0.5767 |
  | 0.1495        | 23.04 | 4400 | 0.9188          | 0.5717 |
  | 0.1276        | 25.13 | 4800 | 1.0149          | 0.5451 |
  | 0.116         | 27.23 | 5200 | 1.0220          | 0.5683 |
  | 0.1017        | 29.32 | 5600 | 0.9319          | 0.5253 |
  | 0.0899        | 31.41 | 6000 | 0.9949          | 0.5435 |
  | 0.0861        | 33.51 | 6400 | 1.1029          | 0.5467 |
  | 0.0766        | 35.6  | 6800 | 1.0219          | 0.5193 |
  | 0.065         | 37.7  | 7200 | 1.0836          | 0.5214 |
  | 0.0588        | 39.79 | 7600 | 1.0713          | 0.5078 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  