readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - filipino_voice
  model-index:
  - name: filipino-wav2vec2-l-xls-r-300m-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. -->
  
  # filipino-wav2vec2-l-xls-r-300m-test
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the filipino_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7753
  - Wer: 0.4831
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.7314        | 2.09  | 400  | 0.7541          | 0.7262 |
  | 0.6065        | 4.19  | 800  | 0.6738          | 0.6314 |
  | 0.4063        | 6.28  | 1200 | 0.6310          | 0.5992 |
  | 0.2986        | 8.38  | 1600 | 0.6301          | 0.5340 |
  | 0.2263        | 10.47 | 2000 | 0.6598          | 0.5391 |
  | 0.1714        | 12.57 | 2400 | 0.7778          | 0.5593 |
  | 0.1303        | 14.66 | 2800 | 0.7231          | 0.4907 |
  | 0.1056        | 16.75 | 3200 | 0.8031          | 0.4885 |
  | 0.0851        | 18.85 | 3600 | 0.7753          | 0.4831 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  