readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - filipino_voice
  model-index:
  - name: filipino-wav2vec2-l-xls-r-300m-official
    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-official
  
  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: 0.4672
  - Wer: 0.2922
  
  ## 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: 0.0003
  - 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.3671        | 2.09  | 400  | 0.5584          | 0.5987 |
  | 0.48          | 4.19  | 800  | 0.4244          | 0.4195 |
  | 0.2796        | 6.28  | 1200 | 0.3742          | 0.3765 |
  | 0.1916        | 8.38  | 1600 | 0.4291          | 0.3667 |
  | 0.1463        | 10.47 | 2000 | 0.3745          | 0.3415 |
  | 0.1165        | 12.57 | 2400 | 0.4472          | 0.3407 |
  | 0.0955        | 14.66 | 2800 | 0.4269          | 0.3290 |
  | 0.0823        | 16.75 | 3200 | 0.4608          | 0.3475 |
  | 0.0709        | 18.85 | 3600 | 0.4706          | 0.3281 |
  | 0.0603        | 20.94 | 4000 | 0.4380          | 0.3183 |
  | 0.0527        | 23.04 | 4400 | 0.4473          | 0.3067 |
  | 0.0449        | 25.13 | 4800 | 0.4550          | 0.3029 |
  | 0.041         | 27.23 | 5200 | 0.4671          | 0.3020 |
  | 0.0358        | 29.32 | 5600 | 0.4672          | 0.2922 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  