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---
license: apache-2.0
tags:
- afro-digits-speech
datasets:
- crowd-speech-africa
metrics:
- accuracy
model-index:
- name: afrospeech-wav2vec-gax
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-gax
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 Oromo (`gax`).
- Size of training set: 32
- Size of validation set: 8
Below is a distribution of the dataset (training and valdation)
## Evaluation performance
It achieves the following results on the [validation set](VALID_oromo_gax_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.
## 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 |
|:-------------:|:-----:|:--------:|
| 0.0699 | 1 | 1.0 |
| 0.0021 | 50 | 0.875 |
| 0.0026 | 100 | 0.875 |
| 0.0017 | 150 | 0.875 |
## Framework versions
- Transformers 4.21.3
- Pytorch 1.12.0
- Datasets 1.14.0
- Tokenizers 0.12.1 |