readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  - robust-speech-event
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-xls-r-300m-Turkish-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-xls-r-300m-Turkish-Tr-med
  
  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: 0.4727
  - Wer: 0.4677
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 4.8093        | 4.21  | 400  | 2.7831          | 1.0    |
  | 0.9881        | 8.42  | 800  | 0.5088          | 0.6681 |
  | 0.3519        | 12.63 | 1200 | 0.4496          | 0.6007 |
  | 0.2436        | 16.84 | 1600 | 0.4993          | 0.5654 |
  | 0.1874        | 21.05 | 2000 | 0.4793          | 0.5530 |
  | 0.1561        | 25.26 | 2400 | 0.5187          | 0.5589 |
  | 0.1336        | 29.47 | 2800 | 0.5135          | 0.5311 |
  | 0.1163        | 33.68 | 3200 | 0.4960          | 0.5143 |
  | 0.1056        | 37.89 | 3600 | 0.4795          | 0.5045 |
  | 0.0959        | 42.11 | 4000 | 0.4883          | 0.4987 |
  | 0.0819        | 46.32 | 4400 | 0.4799          | 0.4903 |
  | 0.0756        | 50.53 | 4800 | 0.4822          | 0.4831 |
  | 0.0692        | 54.74 | 5200 | 0.4621          | 0.4762 |
  | 0.062         | 58.95 | 5600 | 0.4727          | 0.4677 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 1.14.0
  - Tokenizers 0.10.3
  