readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: wav2vec2-base-timit-finetune-3
    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-timit-finetune-3
  
  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: 0.4387
  - Wer: 0.2750
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 60
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.4692        | 6.94  | 500  | 0.9978          | 0.7091 |
  | 0.3946        | 13.88 | 1000 | 0.3674          | 0.3253 |
  | 0.1291        | 20.83 | 1500 | 0.3987          | 0.3042 |
  | 0.074         | 27.77 | 2000 | 0.4292          | 0.2916 |
  | 0.0487        | 34.72 | 2500 | 0.4302          | 0.2853 |
  | 0.0368        | 41.66 | 3000 | 0.4222          | 0.2789 |
  | 0.0281        | 48.61 | 3500 | 0.4481          | 0.2783 |
  | 0.0237        | 55.55 | 4000 | 0.4387          | 0.2750 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1
  - Datasets 2.7.0
  - Tokenizers 0.11.0
  