readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-owndata
    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-owndata
  
  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: 0.2515
  - Wer: 0.3212
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 8
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 4.262         | 0.36  | 100  | 3.4482          | 0.9832 |
  | 3.0032        | 0.72  | 200  | 2.9441          | 0.9832 |
  | 2.9141        | 1.08  | 300  | 2.9393          | 0.9832 |
  | 2.8585        | 1.44  | 400  | 2.8848          | 0.9627 |
  | 2.2837        | 1.8   | 500  | 2.1732          | 1.0111 |
  | 0.9834        | 2.16  | 600  | 0.8765          | 0.7345 |
  | 0.7288        | 2.52  | 700  | 0.5741          | 0.5641 |
  | 0.5521        | 2.88  | 800  | 0.3937          | 0.4467 |
  | 0.3751        | 3.24  | 900  | 0.3484          | 0.4112 |
  | 0.3733        | 3.6   | 1000 | 0.2964          | 0.3912 |
  | 0.2443        | 3.96  | 1100 | 0.2673          | 0.3446 |
  | 0.2667        | 4.32  | 1200 | 0.2657          | 0.3357 |
  | 0.2237        | 4.68  | 1300 | 0.2515          | 0.3212 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.1
  - Datasets 2.9.0
  - Tokenizers 0.10.3
  