metadata
license: apache-2.0
tags:
- afro-digits-speech
datasets:
- crowd-speech-africa
metrics:
- accuracy
model-index:
- name: afrospeech-wav2vec-yor
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: 0.83
afrospeech-wav2vec-yor
This model is a fine-tuned version of facebook/wav2vec2-base on the crowd-speech-africa, which was a crowd-sourced dataset collected using the afro-speech Space. It achieves the following results on the validation set:
- F1: 0.83
- Accuracy: 0.83
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.
Training and evaluation data
The model was trained on a mixed audio data from Yoruba (yor).
- Size of training set: 22
- Size of validation set: 6
Below is a distribution of the dataset (training and valdation)
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 |
|---|---|---|
| 0.596 | 1 | 0.5 |
| 0.0220 | 50 | 0.5 |
| 0.00305 | 100 | 0.667 |
| 0.0993 | 150 | 0.667 |
Framework versions
- Transformers 4.21.3
- Pytorch 1.12.0
- Datasets 1.14.0
- Tokenizers 0.12.1