readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-xls-r-300m-tonga-test_v2
    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-xls-r-300m-tonga-test_v2
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4784
  - Wer: 0.3887
  - Cer: 0.0940
  
  ## 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: 3e-05
  - train_batch_size: 2
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 8
  - 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    | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
  | 6.6795        | 3.62  | 500  | 2.9371          | 1.0    | 1.0    |
  | 2.9201        | 7.25  | 1000 | 2.8427          | 1.0    | 1.0    |
  | 2.6938        | 10.87 | 1500 | 1.6109          | 1.0    | 0.3506 |
  | 1.1605        | 14.49 | 2000 | 0.6472          | 0.5433 | 0.1229 |
  | 0.7598        | 18.12 | 2500 | 0.5543          | 0.4611 | 0.1092 |
  | 0.6529        | 21.74 | 3000 | 0.5202          | 0.4289 | 0.1026 |
  | 0.5816        | 25.36 | 3500 | 0.4931          | 0.4093 | 0.0981 |
  | 0.5476        | 28.98 | 4000 | 0.4916          | 0.4041 | 0.0978 |
  | 0.517         | 32.61 | 4500 | 0.4765          | 0.3948 | 0.0951 |
  | 0.5025        | 36.23 | 5000 | 0.4812          | 0.3879 | 0.0942 |
  | 0.4879        | 39.85 | 5500 | 0.4784          | 0.3887 | 0.0940 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  