readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-300m-vi-75p
    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. -->
  
  # wav2vec2-large-xls-r-300m-vi-75p
  
  This model is a fine-tuned version of [leviethoang/wav2vec2-large-xls-r-300m-vi-25p](https://huggingface.co/leviethoang/wav2vec2-large-xls-r-300m-vi-25p) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.7880
  - Wer: 0.4324
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.962         | 1.68  | 400  | 1.2033          | 0.4428 |
  | 0.7977        | 3.36  | 800  | 1.3410          | 0.4731 |
  | 0.644         | 5.04  | 1200 | 1.4682          | 0.4796 |
  | 0.5156        | 6.72  | 1600 | 1.4940          | 0.4826 |
  | 0.4531        | 8.4   | 2000 | 1.5071          | 0.4734 |
  | 0.3882        | 10.08 | 2400 | 1.5408          | 0.4694 |
  | 0.3469        | 11.76 | 2800 | 1.5975          | 0.4697 |
  | 0.3096        | 13.45 | 3200 | 1.7120          | 0.4728 |
  | 0.2825        | 15.13 | 3600 | 1.7052          | 0.4632 |
  | 0.2607        | 16.81 | 4000 | 1.6870          | 0.4575 |
  | 0.2301        | 18.49 | 4400 | 1.7205          | 0.4653 |
  | 0.2096        | 20.17 | 4800 | 1.7352          | 0.4504 |
  | 0.1915        | 21.85 | 5200 | 1.7948          | 0.4465 |
  | 0.1685        | 23.53 | 5600 | 1.7994          | 0.4400 |
  | 0.1543        | 25.21 | 6000 | 1.7613          | 0.4435 |
  | 0.1378        | 26.89 | 6400 | 1.8300          | 0.4365 |
  | 0.1278        | 28.57 | 6800 | 1.7880          | 0.4324 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  