readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: wav2vec2-base-finetuned-ks
    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-finetuned-ks
  
  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: 0.2562
  - Accuracy: 0.9869
  
  ## 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: 3e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 16
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 2.4691        | 0.99  | 26   | 2.3935          | 0.2310   |
  | 2.1621        | 1.99  | 52   | 2.0155          | 0.3202   |
  | 1.8731        | 2.99  | 78   | 1.6397          | 0.7929   |
  | 1.4521        | 3.99  | 104  | 1.2337          | 0.8940   |
  | 1.101         | 4.99  | 130  | 0.9519          | 0.9393   |
  | 0.9401        | 5.99  | 156  | 0.7686          | 0.975    |
  | 0.7463        | 6.99  | 182  | 0.6338          | 0.9774   |
  | 0.6555        | 7.99  | 208  | 0.5214          | 0.9810   |
  | 0.5095        | 8.99  | 234  | 0.4228          | 0.9869   |
  | 0.4152        | 9.99  | 260  | 0.3658          | 0.9857   |
  | 0.3764        | 10.99 | 286  | 0.3311          | 0.9857   |
  | 0.3325        | 11.99 | 312  | 0.2954          | 0.9881   |
  | 0.3121        | 12.99 | 338  | 0.2797          | 0.9869   |
  | 0.281         | 13.99 | 364  | 0.2650          | 0.9857   |
  | 0.2627        | 14.99 | 390  | 0.2571          | 0.9869   |
  | 0.2655        | 15.99 | 416  | 0.2562          | 0.9869   |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.1+cu113
  - Datasets 1.14.0
  - Tokenizers 0.12.1
  