readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-base
    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-base
  
  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: 3.0808
  - Wer: 1.0
  
  ## 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: 4
  - 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: 15
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer |
  |:-------------:|:-----:|:-----:|:---------------:|:---:|
  | 3.7118        | 0.5   | 500   | 3.0635          | 1.0 |
  | 2.9533        | 1.01  | 1000  | 3.0383          | 1.0 |
  | 2.9493        | 1.51  | 1500  | 3.0638          | 1.0 |
  | 2.9495        | 2.01  | 2000  | 3.0554          | 1.0 |
  | 2.9468        | 2.51  | 2500  | 3.0630          | 1.0 |
  | 2.9493        | 3.02  | 3000  | 3.0530          | 1.0 |
  | 2.9457        | 3.52  | 3500  | 3.0534          | 1.0 |
  | 2.9492        | 4.02  | 4000  | 3.0357          | 1.0 |
  | 2.9444        | 4.52  | 4500  | 3.0366          | 1.0 |
  | 2.9495        | 5.03  | 5000  | 3.0412          | 1.0 |
  | 2.9468        | 5.53  | 5500  | 3.0331          | 1.0 |
  | 2.9453        | 6.03  | 6000  | 3.0847          | 1.0 |
  | 2.9484        | 6.53  | 6500  | 3.0661          | 1.0 |
  | 2.9457        | 7.04  | 7000  | 3.0769          | 1.0 |
  | 2.9449        | 7.54  | 7500  | 3.0701          | 1.0 |
  | 2.9453        | 8.04  | 8000  | 3.1072          | 1.0 |
  | 2.9436        | 8.54  | 8500  | 3.1043          | 1.0 |
  | 2.9474        | 9.05  | 9000  | 3.0902          | 1.0 |
  | 2.9452        | 9.55  | 9500  | 3.0879          | 1.0 |
  | 2.9443        | 10.05 | 10000 | 3.1112          | 1.0 |
  | 2.9436        | 10.55 | 10500 | 3.0946          | 1.0 |
  | 2.9469        | 11.06 | 11000 | 3.0812          | 1.0 |
  | 2.9434        | 11.56 | 11500 | 3.1112          | 1.0 |
  | 2.9442        | 12.06 | 12000 | 3.0855          | 1.0 |
  | 2.9436        | 12.56 | 12500 | 3.0786          | 1.0 |
  | 2.9425        | 13.07 | 13000 | 3.0789          | 1.0 |
  | 2.9418        | 13.57 | 13500 | 3.0786          | 1.0 |
  | 2.9443        | 14.07 | 14000 | 3.0798          | 1.0 |
  | 2.9449        | 14.57 | 14500 | 3.0808          | 1.0 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.2
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  