readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: wav2vec2-base-POSITIVE_NEGATIVE_ONLY_BALANCED_CLASSES
    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-POSITIVE_NEGATIVE_ONLY_BALANCED_CLASSES
  
  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: 0.3710
  - Accuracy: 0.8822
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 256
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.7822        | 0.96  | 18   | 0.6874          | 0.7424   |
  | 0.5685        | 1.96  | 36   | 0.5974          | 0.7845   |
  | 0.45          | 2.96  | 54   | 0.4988          | 0.8182   |
  | 0.399         | 3.96  | 72   | 0.4583          | 0.8384   |
  | 0.3457        | 4.96  | 90   | 0.4415          | 0.8451   |
  | 0.352         | 5.96  | 108  | 0.3710          | 0.8822   |
  | 0.2878        | 6.96  | 126  | 0.3881          | 0.8620   |
  | 0.2669        | 7.96  | 144  | 0.4309          | 0.8502   |
  | 0.2406        | 8.96  | 162  | 0.4271          | 0.8502   |
  | 0.2491        | 9.96  | 180  | 0.4271          | 0.8502   |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.11.0
  - Datasets 1.14.0
  - Tokenizers 0.10.3
  