readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-300m-vi-colab-all
    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-colab-all
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: inf
  - Wer: 0.4537
  
  ## 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: 0.0001
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 7.448         | 2.4   | 400  | inf             | 1.0    |
  | 2.8589        | 4.79  | 800  | inf             | 0.7777 |
  | 1.4919        | 7.19  | 1200 | inf             | 0.5968 |
  | 1.1255        | 9.58  | 1600 | inf             | 0.5540 |
  | 0.9354        | 11.98 | 2000 | inf             | 0.4970 |
  | 0.7816        | 14.37 | 2400 | inf             | 0.4799 |
  | 0.6822        | 16.77 | 2800 | inf             | 0.4785 |
  | 0.5768        | 19.16 | 3200 | inf             | 0.4704 |
  | 0.5031        | 21.56 | 3600 | inf             | 0.4609 |
  | 0.4589        | 23.95 | 4000 | inf             | 0.4585 |
  | 0.4136        | 26.35 | 4400 | inf             | 0.4592 |
  | 0.3829        | 28.74 | 4800 | inf             | 0.4537 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  