readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice_1_0
  model-index:
  - name: dat259-wav2vec2-en2
    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. -->
  
  # dat259-wav2vec2-en2
  
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the common_voice_1_0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4036
  - Wer: 0.5090
  
  ## 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
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 300
  - num_epochs: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 4.4355        | 1.82  | 200  | 3.0307          | 1.0    |
  | 2.1744        | 3.64  | 400  | 1.5661          | 0.7449 |
  | 0.5535        | 5.45  | 600  | 1.3005          | 0.5914 |
  | 0.3248        | 7.27  | 800  | 1.2481          | 0.5690 |
  | 0.2297        | 9.09  | 1000 | 1.2810          | 0.5366 |
  | 0.18          | 10.91 | 1200 | 1.3481          | 0.5378 |
  | 0.1499        | 12.73 | 1400 | 1.3124          | 0.5350 |
  | 0.1283        | 14.55 | 1600 | 1.3668          | 0.5161 |
  | 0.1089        | 16.36 | 1800 | 1.3833          | 0.5109 |
  | 0.0973        | 18.18 | 2000 | 1.3876          | 0.5075 |
  | 0.0897        | 20.0  | 2200 | 1.4036          | 0.5090 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.1+cu102
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  