readme: ---
  license: apache-2.0
  tags:
  - afro-digits-speech
  datasets:
  - crowd-speech-africa
  metrics:
  - accuracy
  model-index:
  - name: afrospeech-wav2vec-sna
    results:
    - task:
        name: Audio Classification 
        type: audio-classification
      dataset:
        name: Afro Speech
        type: chrisjay/crowd-speech-africa
        args: no
      metrics:
         - name: Validation Accuracy
           type: accuracy
           value: 1.0
  ---
  
  
  # afrospeech-wav2vec-sna
  
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the [crowd-speech-africa](https://huggingface.co/datasets/chrisjay/crowd-speech-africa), which was a crowd-sourced dataset collected using the [afro-speech Space](https://huggingface.co/spaces/chrisjay/afro-speech). 
  
  ## Training and evaluation data
  
  The model was trained on a mixed audio data from Shona (`sna`).
  
  - Size of training set: 24
  - Size of validation set: 6
  
  Below is a distribution of the dataset (training and valdation) 
  
  ![digits-bar-plot-for-afrospeech](digits-bar-plot-for-afrospeech-wav2vec-sna.png)
  
  ## Evaluation performance
  It achieves the following results on the [validation set](VALID_shona_sna_audio_data.csv):
  - F1: 1.0
  - Accuracy: 1.0
  
  The confusion matrix below helps to give a better look at the model's performance across the digits. Through it, we can see the precision and recall of the model as well as other important insights. 
  
  ![confusion matrix](afrospeech-wav2vec-sna_confusion_matrix_VALID.png)
  
  
  
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 3e-05
  - train_batch_size: 64
  - eval_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - num_epochs: 150
  
  ### Training results
  
  | Training Loss | Epoch |  Validation Accuracy |
  |:-------------:|:-----:|:--------:|
  | 0.02387        | 1    | 1.0 |
  | 0.0021066       | 50   | 1.0 |
  | 0.001157       | 100   | 1.0  |
  | 0.0009537       | 150   | 1.0  |
  
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.0
  - Datasets 1.14.0
  - Tokenizers 0.12.1