readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: xlsr-wav2vec2-1
    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. -->
  
  # xlsr-wav2vec2-1
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5437
  - Wer: 0.4412
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 800
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 5.517         | 1.38  | 400  | 3.0431          | 1.0    |
  | 1.8387        | 2.76  | 800  | 0.6552          | 0.7263 |
  | 0.5971        | 4.14  | 1200 | 0.5308          | 0.5885 |
  | 0.4153        | 5.52  | 1600 | 0.4667          | 0.5551 |
  | 0.3388        | 6.9   | 2000 | 0.4428          | 0.5260 |
  | 0.2803        | 8.28  | 2400 | 0.4915          | 0.5164 |
  | 0.2613        | 9.65  | 2800 | 0.4904          | 0.4988 |
  | 0.237         | 11.03 | 3200 | 0.4998          | 0.5075 |
  | 0.2175        | 12.41 | 3600 | 0.4905          | 0.4983 |
  | 0.1969        | 13.79 | 4000 | 0.4818          | 0.4877 |
  | 0.1932        | 15.17 | 4400 | 0.5578          | 0.5006 |
  | 0.1782        | 16.55 | 4800 | 0.4981          | 0.4949 |
  | 0.1655        | 17.93 | 5200 | 0.4978          | 0.4940 |
  | 0.1505        | 19.31 | 5600 | 0.5360          | 0.4896 |
  | 0.1362        | 20.69 | 6000 | 0.5441          | 0.4709 |
  | 0.1246        | 22.07 | 6400 | 0.5358          | 0.4650 |
  | 0.1117        | 23.45 | 6800 | 0.5513          | 0.4716 |
  | 0.107         | 24.83 | 7200 | 0.5344          | 0.4578 |
  | 0.0963        | 26.21 | 7600 | 0.5073          | 0.4452 |
  | 0.0846        | 27.59 | 8000 | 0.5335          | 0.4497 |
  | 0.0799        | 28.96 | 8400 | 0.5437          | 0.4412 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  