readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-base-librispeech100h-google-colab
    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-librispeech100h-google-colab
  
  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: 0.1156
  - Wer: 0.0756
  
  ## 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: 16
  - 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: 500
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1.6033        | 0.9   | 1600 | 0.4802          | 0.2728 |
  | 0.1912        | 1.79  | 3200 | 0.1601          | 0.1140 |
  | 0.1409        | 2.69  | 4800 | 0.1423          | 0.0932 |
  | 0.108         | 3.59  | 6400 | 0.1260          | 0.0806 |
  | 0.1045        | 4.48  | 8000 | 0.1156          | 0.0756 |
  
  
  ### Framework versions
  
  - Transformers 4.20.0.dev0
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.3.dev0
  - Tokenizers 0.12.1
  