readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: wav2vec2-large-teacher-base-student-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-large-teacher-base-student-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: 73.5882
  - Wer: 0.3422
  
  ## 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: 64
  - 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 920.6083      | 3.17  | 200  | 1256.0675       | 1.0    |
  | 660.5993      | 6.35  | 400  | 717.6098        | 0.9238 |
  | 336.5288      | 9.52  | 600  | 202.0025        | 0.5306 |
  | 131.3178      | 12.7  | 800  | 108.0701        | 0.4335 |
  | 73.4232       | 15.87 | 1000 | 90.2797         | 0.3728 |
  | 54.9439       | 19.05 | 1200 | 76.9043         | 0.3636 |
  | 44.6595       | 22.22 | 1400 | 79.2443         | 0.3550 |
  | 38.6381       | 25.4  | 1600 | 73.6277         | 0.3493 |
  | 35.074        | 28.57 | 1800 | 73.5882         | 0.3422 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  