readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  - robust-speech-event
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xlsr-53-W2V2-TR-MED
    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-xlsr-53-W2V2-TR-MED
  
  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: 0.4467
  - Wer: 0.4598
  
  ## 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: 60
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 5.1343        | 4.21  | 400  | 2.3674          | 1.0372 |
  | 0.8075        | 8.42  | 800  | 0.4583          | 0.6308 |
  | 0.3209        | 12.63 | 1200 | 0.4291          | 0.5531 |
  | 0.2273        | 16.84 | 1600 | 0.4348          | 0.5378 |
  | 0.1764        | 21.05 | 2000 | 0.4550          | 0.5326 |
  | 0.148         | 25.26 | 2400 | 0.4839          | 0.5319 |
  | 0.1268        | 29.47 | 2800 | 0.4515          | 0.5070 |
  | 0.1113        | 33.68 | 3200 | 0.4590          | 0.4930 |
  | 0.1025        | 37.89 | 3600 | 0.4546          | 0.4888 |
  | 0.0922        | 42.11 | 4000 | 0.4782          | 0.4852 |
  | 0.082         | 46.32 | 4400 | 0.4605          | 0.4752 |
  | 0.0751        | 50.53 | 4800 | 0.4358          | 0.4689 |
  | 0.0699        | 54.74 | 5200 | 0.4359          | 0.4629 |
  | 0.0633        | 58.95 | 5600 | 0.4467          | 0.4598 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 1.14.0
  - Tokenizers 0.10.3
  