readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: wav2vec2-base-en-asr-timit
    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-en-asr-timit
  
  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: 0.4525
  - Wer: 0.3510
  
  ## 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: 64
  - 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 4.6253        | 3.17  | 200  | 3.0613          | 1.0    |
  | 2.9038        | 6.35  | 400  | 2.7513          | 1.0    |
  | 1.5048        | 9.52  | 600  | 0.6193          | 0.5702 |
  | 0.4196        | 12.7  | 800  | 0.4788          | 0.4464 |
  | 0.2203        | 15.87 | 1000 | 0.4743          | 0.4098 |
  | 0.1439        | 19.05 | 1200 | 0.4420          | 0.3804 |
  | 0.0963        | 22.22 | 1400 | 0.4587          | 0.3620 |
  | 0.073         | 25.4  | 1600 | 0.4681          | 0.3588 |
  | 0.0603        | 28.57 | 1800 | 0.4525          | 0.3510 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  