readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec_trained
    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. -->
  
  # wav2vec_trained
  
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0337
  - Wer: 0.1042
  
  ## 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: 0.0001
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 4.3849        | 2.21  | 500  | 2.9148          | 1.0    |
  | 1.9118        | 4.42  | 1000 | 0.9627          | 0.5833 |
  | 0.7596        | 6.64  | 1500 | 0.8953          | 0.3542 |
  | 0.4602        | 8.85  | 2000 | 0.3325          | 0.2083 |
  | 0.331         | 11.06 | 2500 | 0.3084          | 0.2083 |
  | 0.2474        | 13.27 | 3000 | 0.0960          | 0.1667 |
  | 0.1934        | 15.49 | 3500 | 0.1276          | 0.125  |
  | 0.156         | 17.7  | 4000 | 0.0605          | 0.0833 |
  | 0.1244        | 19.91 | 4500 | 0.0831          | 0.1458 |
  | 0.1006        | 22.12 | 5000 | 0.0560          | 0.125  |
  | 0.0827        | 24.34 | 5500 | 0.0395          | 0.0833 |
  | 0.0723        | 26.55 | 6000 | 0.0573          | 0.0833 |
  | 0.0606        | 28.76 | 6500 | 0.0337          | 0.1042 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  