readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - filipino_voice
  model-index:
  - name: english-filipino-wav2vec2-l-xls-r-test-03
    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-03
  
  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: 0.6932
  - Wer: 0.3676
  
  ## 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: 40
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.3398        | 2.09  | 400  | 0.5733          | 0.6166 |
  | 0.5087        | 4.19  | 800  | 0.5210          | 0.4775 |
  | 0.344         | 6.28  | 1200 | 0.5284          | 0.5008 |
  | 0.2745        | 8.38  | 1600 | 0.5195          | 0.4457 |
  | 0.2153        | 10.47 | 2000 | 0.5820          | 0.4668 |
  | 0.1797        | 12.57 | 2400 | 0.4915          | 0.4432 |
  | 0.1513        | 14.66 | 2800 | 0.6316          | 0.4513 |
  | 0.1355        | 16.75 | 3200 | 0.5328          | 0.4070 |
  | 0.1204        | 18.85 | 3600 | 0.5800          | 0.4405 |
  | 0.1062        | 20.94 | 4000 | 0.6887          | 0.4532 |
  | 0.0931        | 23.04 | 4400 | 0.6184          | 0.4152 |
  | 0.0821        | 25.13 | 4800 | 0.7413          | 0.4461 |
  | 0.0733        | 27.23 | 5200 | 0.7160          | 0.4549 |
  | 0.071         | 29.32 | 5600 | 0.7001          | 0.4048 |
  | 0.0577        | 31.41 | 6000 | 0.7839          | 0.4309 |
  | 0.051         | 33.51 | 6400 | 0.7764          | 0.4128 |
  | 0.046         | 35.6  | 6800 | 0.6753          | 0.3875 |
  | 0.0384        | 37.7  | 7200 | 0.7106          | 0.3856 |
  | 0.0359        | 39.79 | 7600 | 0.6932          | 0.3676 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  