metadata
license: apache-2.0
tags:
- afro-digits-speech
datasets:
- crowd-speech-africa
metrics:
- accuracy
model-index:
- name: afrospeech-wav2vec-all-6
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: 0.6205
afrospeech-wav2vec-all-6
This model is a fine-tuned version of facebook/wav2vec2-base on the crowd-speech-africa. It achieves the following results on the validation set:
- F1: 0.5787048581502744
- Accuracy: 0.6205357142857143
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.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
- Size of training set: 1977
- Size of validation set: 396
Training procedure
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 |
---|---|---|
2.0466 | 1 | 0.1130 |
0.0468 | 50 | 0.6116 |
0.0292 | 100 | 0.5305 |
0.0155 | 150 | 0.5319 |
Framework versions
- Transformers 4.21.3
- Pytorch 1.12.0
- Datasets 1.14.0
- Tokenizers 0.12.1