readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  metrics:
  - wer
  model-index:
  - name: outputs
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: common_voice
        type: common_voice
        config: tr
        split: train+validation
        args: tr
      metrics:
      - name: Wer
        type: wer
        value: 0.35818608926565215
  ---
  
  <!-- 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. -->
  
  # outputs
  
  This model was trained from scratch on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3878
  - Wer: 0.3582
  
  ## 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: 64
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 5
  - num_epochs: 1.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.7391        | 0.92  | 100  | 3.5760          | 1.0    |
  | 2.927         | 1.83  | 200  | 3.0796          | 0.9999 |
  | 0.9009        | 2.75  | 300  | 0.9278          | 0.8226 |
  | 0.6529        | 3.67  | 400  | 0.5926          | 0.6367 |
  | 0.3623        | 4.59  | 500  | 0.5372          | 0.5692 |
  | 0.2888        | 5.5   | 600  | 0.4407          | 0.4838 |
  | 0.285         | 6.42  | 700  | 0.4341          | 0.4694 |
  | 0.0842        | 7.34  | 800  | 0.4153          | 0.4302 |
  | 0.1415        | 8.26  | 900  | 0.4317          | 0.4136 |
  | 0.1552        | 9.17  | 1000 | 0.4145          | 0.4013 |
  | 0.1184        | 10.09 | 1100 | 0.4115          | 0.3844 |
  | 0.0556        | 11.01 | 1200 | 0.4182          | 0.3862 |
  | 0.0851        | 11.93 | 1300 | 0.3985          | 0.3688 |
  | 0.0961        | 12.84 | 1400 | 0.4030          | 0.3665 |
  | 0.0596        | 13.76 | 1500 | 0.3880          | 0.3631 |
  | 0.0917        | 14.68 | 1600 | 0.3878          | 0.3582 |
  
  
  ### Framework versions
  
  - Transformers 4.25.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  