readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: Nystrom-W2V2-100hrs-take-2
    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. -->
  
  # Nystrom-W2V2-100hrs-take-2
  
  This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 26.8554
  - Wer: 0.1392
  
  ## 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: 0.0005
  - train_batch_size: 4
  - eval_batch_size: 1
  - seed: 42
  - gradient_accumulation_steps: 32
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_ratio: 0.2
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1090.0902     | 4.5   | 1000 | 54.4575         | 0.4841 |
  | 307.7589      | 9.01  | 2000 | 29.7460         | 0.2633 |
  | 170.6373      | 13.51 | 3000 | 25.5445         | 0.1984 |
  | 113.7445      | 18.02 | 4000 | 24.8862         | 0.1696 |
  | 78.7363       | 22.52 | 5000 | 25.9566         | 0.1494 |
  | 59.5531       | 27.03 | 6000 | 26.8554         | 0.1392 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.11.0
  