readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - filipino_voice
  model-index:
  - name: english-filipino-wav2vec2-l-xls-r-test-06
    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-06
  
  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: 1.5806
  - Wer: 0.6568
  
  ## 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: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.0031        | 2.09  | 400  | 1.2366          | 0.8780 |
  | 0.9084        | 4.19  | 800  | 1.0653          | 0.8081 |
  | 0.6484        | 6.28  | 1200 | 1.1648          | 0.8258 |
  | 0.5335        | 8.38  | 1600 | 1.0903          | 0.7542 |
  | 0.4359        | 10.47 | 2000 | 0.9466          | 0.7058 |
  | 0.3629        | 12.57 | 2400 | 0.9266          | 0.7048 |
  | 0.3057        | 14.66 | 2800 | 1.0879          | 0.7018 |
  | 0.2477        | 16.75 | 3200 | 1.1113          | 0.7022 |
  | 0.208         | 18.85 | 3600 | 1.1345          | 0.6742 |
  | 0.1781        | 20.94 | 4000 | 1.3117          | 0.6974 |
  | 0.1465        | 23.04 | 4400 | 1.3248          | 0.6916 |
  | 0.1288        | 25.13 | 4800 | 1.4306          | 0.6523 |
  | 0.1108        | 27.23 | 5200 | 1.5155          | 0.6685 |
  | 0.099         | 29.32 | 5600 | 1.5806          | 0.6568 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  