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: 0.5766
  - Accuracy: 0.8308
  
  ## 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: 1.5e-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: 15
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 7    | 0.7247          | 0.7462   |
  | No log        | 2.0   | 14   | 0.6844          | 0.7615   |
  | 0.4279        | 3.0   | 21   | 0.7254          | 0.7462   |
  | 0.4279        | 4.0   | 28   | 0.5891          | 0.8      |
  | 0.4279        | 5.0   | 35   | 0.6991          | 0.7462   |
  | 0.4478        | 6.0   | 42   | 0.6579          | 0.7615   |
  | 0.4478        | 7.0   | 49   | 0.6164          | 0.8      |
  | 0.4478        | 8.0   | 56   | 0.6191          | 0.8077   |
  | 0.4194        | 9.0   | 63   | 0.5766          | 0.8308   |
  | 0.4194        | 10.0  | 70   | 0.5704          | 0.8154   |
  | 0.4194        | 11.0  | 77   | 0.6518          | 0.8      |
  | 0.3833        | 12.0  | 84   | 0.6190          | 0.8077   |
  | 0.3833        | 13.0  | 91   | 0.5693          | 0.8231   |
  | 0.3833        | 14.0  | 98   | 0.5628          | 0.8231   |
  | 0.3607        | 15.0  | 105  | 0.5741          | 0.8154   |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.10.3
  