readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-base_toy_train_data_augmented
    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_toy_train_data_augmented
  
  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: 1.0238
  - Wer: 0.6969
  
  ## 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
  - 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: 1000
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.12          | 1.05  | 250  | 3.3998          | 0.9982 |
  | 3.0727        | 2.1   | 500  | 3.1261          | 0.9982 |
  | 1.9729        | 3.15  | 750  | 1.4868          | 0.9464 |
  | 1.3213        | 4.2   | 1000 | 1.2598          | 0.8833 |
  | 1.0508        | 5.25  | 1250 | 1.0014          | 0.8102 |
  | 0.8483        | 6.3   | 1500 | 0.9475          | 0.7944 |
  | 0.7192        | 7.35  | 1750 | 0.9493          | 0.7686 |
  | 0.6447        | 8.4   | 2000 | 0.9872          | 0.7573 |
  | 0.6064        | 9.45  | 2250 | 0.9587          | 0.7447 |
  | 0.5384        | 10.5  | 2500 | 0.9332          | 0.7320 |
  | 0.4985        | 11.55 | 2750 | 0.9926          | 0.7315 |
  | 0.4643        | 12.6  | 3000 | 1.0008          | 0.7292 |
  | 0.4565        | 13.65 | 3250 | 0.9522          | 0.7171 |
  | 0.449         | 14.7  | 3500 | 0.9685          | 0.7140 |
  | 0.4307        | 15.75 | 3750 | 1.0080          | 0.7077 |
  | 0.4239        | 16.81 | 4000 | 0.9950          | 0.7023 |
  | 0.389         | 17.86 | 4250 | 1.0260          | 0.7007 |
  | 0.3471        | 18.91 | 4500 | 1.0012          | 0.6966 |
  | 0.3276        | 19.96 | 4750 | 1.0238          | 0.6969 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu102
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  