readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-hun-53h-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-hun-53h-colab
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6027
  - Wer: 0.4618
  
  ## 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: 23
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 13.4225       | 0.67  | 100  | 3.7750          | 1.0    |
  | 3.4121        | 1.34  | 200  | 3.3166          | 1.0    |
  | 3.2263        | 2.01  | 300  | 3.1403          | 1.0    |
  | 3.0038        | 2.68  | 400  | 2.2474          | 0.9990 |
  | 1.2243        | 3.35  | 500  | 0.8174          | 0.7666 |
  | 0.6368        | 4.03  | 600  | 0.6306          | 0.6633 |
  | 0.4426        | 4.7   | 700  | 0.6151          | 0.6648 |
  | 0.3821        | 5.37  | 800  | 0.5765          | 0.6138 |
  | 0.3337        | 6.04  | 900  | 0.5522          | 0.5785 |
  | 0.2832        | 6.71  | 1000 | 0.5822          | 0.5691 |
  | 0.2485        | 7.38  | 1100 | 0.5626          | 0.5449 |
  | 0.2335        | 8.05  | 1200 | 0.5866          | 0.5662 |
  | 0.2031        | 8.72  | 1300 | 0.5574          | 0.5420 |
  | 0.1925        | 9.39  | 1400 | 0.5572          | 0.5297 |
  | 0.1793        | 10.07 | 1500 | 0.5878          | 0.5185 |
  | 0.1652        | 10.74 | 1600 | 0.6173          | 0.5243 |
  | 0.1663        | 11.41 | 1700 | 0.5807          | 0.5133 |
  | 0.1544        | 12.08 | 1800 | 0.5979          | 0.5154 |
  | 0.148         | 12.75 | 1900 | 0.5545          | 0.4986 |
  | 0.138         | 13.42 | 2000 | 0.5798          | 0.4947 |
  | 0.1353        | 14.09 | 2100 | 0.5670          | 0.5028 |
  | 0.1283        | 14.76 | 2200 | 0.5862          | 0.4957 |
  | 0.1271        | 15.43 | 2300 | 0.6009          | 0.4961 |
  | 0.1108        | 16.11 | 2400 | 0.5873          | 0.4975 |
  | 0.1182        | 16.78 | 2500 | 0.6013          | 0.4893 |
  | 0.103         | 17.45 | 2600 | 0.6165          | 0.4898 |
  | 0.1084        | 18.12 | 2700 | 0.6186          | 0.4838 |
  | 0.1014        | 18.79 | 2800 | 0.6122          | 0.4767 |
  | 0.1009        | 19.46 | 2900 | 0.5981          | 0.4793 |
  | 0.1004        | 20.13 | 3000 | 0.6034          | 0.4770 |
  | 0.0922        | 20.8  | 3100 | 0.6127          | 0.4663 |
  | 0.09          | 21.47 | 3200 | 0.5967          | 0.4672 |
  | 0.0893        | 22.15 | 3300 | 0.6051          | 0.4611 |
  | 0.0817        | 22.82 | 3400 | 0.6027          | 0.4618 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  