readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-300m-turkish-colab_common_voice-8_4
    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-turkish-colab_common_voice-8_4
  
  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: 0.3201
  - Wer: 0.3295
  
  ## 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: 11
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 5.9268        | 0.51  | 400  | 1.3204          | 0.9175 |
  | 0.7491        | 1.02  | 800  | 0.5880          | 0.6388 |
  | 0.4911        | 1.53  | 1200 | 0.4680          | 0.5613 |
  | 0.4265        | 2.04  | 1600 | 0.4213          | 0.5059 |
  | 0.3473        | 2.55  | 2000 | 0.4199          | 0.4955 |
  | 0.3291        | 3.07  | 2400 | 0.4323          | 0.5061 |
  | 0.2819        | 3.58  | 2800 | 0.4026          | 0.4490 |
  | 0.2628        | 4.09  | 3200 | 0.3831          | 0.4446 |
  | 0.2371        | 4.6   | 3600 | 0.3622          | 0.4234 |
  | 0.2274        | 5.11  | 4000 | 0.3473          | 0.4012 |
  | 0.2051        | 5.62  | 4400 | 0.3471          | 0.3998 |
  | 0.1985        | 6.13  | 4800 | 0.3759          | 0.4088 |
  | 0.1767        | 6.64  | 5200 | 0.3620          | 0.4012 |
  | 0.1707        | 7.15  | 5600 | 0.3415          | 0.3700 |
  | 0.1559        | 7.66  | 6000 | 0.3317          | 0.3661 |
  | 0.147         | 8.17  | 6400 | 0.3265          | 0.3618 |
  | 0.1339        | 8.68  | 6800 | 0.3293          | 0.3586 |
  | 0.126         | 9.2   | 7200 | 0.3386          | 0.3458 |
  | 0.1149        | 9.71  | 7600 | 0.3305          | 0.3397 |
  | 0.1051        | 10.22 | 8000 | 0.3235          | 0.3354 |
  | 0.1005        | 10.73 | 8400 | 0.3201          | 0.3295 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.10.3
  