readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice_10_0
  model-index:
  - name: wav2vec2-large-xls-r-300m-j-phoneme-colab
    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-j-phoneme-colab
  
  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_10_0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5212
  - Wer: 0.2998
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 4
  - 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 0.7364        | 3.0   | 2000  | 0.4703          | 0.4503 |
  | 0.5673        | 6.01  | 4000  | 0.4585          | 0.3855 |
  | 0.5048        | 9.01  | 6000  | 0.4567          | 0.3543 |
  | 0.4567        | 12.01 | 8000  | 0.4433          | 0.3473 |
  | 0.4194        | 15.02 | 10000 | 0.4491          | 0.3386 |
  | 0.3905        | 18.02 | 12000 | 0.4829          | 0.3360 |
  | 0.3644        | 21.02 | 14000 | 0.5032          | 0.3306 |
  | 0.3441        | 24.02 | 16000 | 0.5242          | 0.3389 |
  | 0.2589        | 27.03 | 18000 | 0.5212          | 0.2998 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.10.0+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  