readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - coscan-speech
  metrics:
  - accuracy
  model-index:
  - name: wav2vec2-base-finetuned-coscan-sex
    results:
    - task:
        name: Audio Classification 
        type: audio-classification
      dataset:
        name: Coscan Speech
        type: NbAiLab/coscan-speech
        args: no
      metrics:
         - name: Test Accuracy
           type: accuracy
           value: 0.9993247805536799
         - name: Validation Accuracy
           type: accuracy
           value: 0.9965283657917019
  ---
  
  <!-- 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-coscan-sex
  
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the coscan-speech dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0229
  - Accuracy: 0.9965
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.0034        | 1.0   | 6644 | 0.0229          | 0.9965   |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.10.1+cu102
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  