readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-300m-hi
    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-hi
  
  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: 2.4156
  - Wer: 0.7181
  
  ## 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: 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
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 5.7703        | 2.72  | 400  | 2.2274          | 0.9259 |
  | 0.6515        | 5.44  | 800  | 1.5812          | 0.7581 |
  | 0.339         | 8.16  | 1200 | 2.0590          | 0.7825 |
  | 0.2262        | 10.88 | 1600 | 2.0324          | 0.7603 |
  | 0.1665        | 13.6  | 2000 | 2.1396          | 0.7481 |
  | 0.1311        | 16.33 | 2400 | 2.2090          | 0.7379 |
  | 0.1079        | 19.05 | 2800 | 2.3907          | 0.7612 |
  | 0.0927        | 21.77 | 3200 | 2.5294          | 0.7478 |
  | 0.0748        | 24.49 | 3600 | 2.5024          | 0.7452 |
  | 0.0644        | 27.21 | 4000 | 2.4715          | 0.7307 |
  | 0.0569        | 29.93 | 4400 | 2.4156          | 0.7181 |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.0+cu111
  - Datasets 1.17.0
  - Tokenizers 0.10.3
  