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README.md
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---
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license: apache-2.0
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tags:
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- afro-digits-speech
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datasets:
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- crowd-speech-africa
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metrics:
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- accuracy
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model-index:
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- name: afrospeech-wav2vec-sna
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results:
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- task:
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name: Audio Classification
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type: audio-classification
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dataset:
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name: Afro Speech
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type: chrisjay/crowd-speech-africa
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args: no
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metrics:
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- name: Validation Accuracy
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type: accuracy
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value: 1.0
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---
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# afrospeech-wav2vec-sna
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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). It achieves the following results on the [validation set](VALID_shona_sna_audio_data.csv):
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- F1: 1.0
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- Accuracy: 1.0
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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.
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![confusion matrix](afrospeech-wav2vec-sna_confusion_matrix_VALID.png)
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## Training and evaluation data
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The model was trained on a mixed audio data from Shona (`sna`).
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- Size of training set: 24
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- Size of validation set: 6
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Below is a distribution of the dataset (training and valdation)
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![digits-bar-plot-for-afrospeech](digits-bar-plot-for-afrospeech-wav2vec-sna.png)
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 64
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- eval_batch_size: 64
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- num_epochs: 150
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### Training results
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| Training Loss | Epoch | Validation Accuracy |
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|:-------------:|:-----:|:--------:|
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| 0.02387 | 1 | 1.0 |
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| 0.0021066 | 50 | 1.0 |
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| 0.001157 | 100 | 1.0 |
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| 0.0009537 | 150 | 1.0 |
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### Framework versions
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- Transformers 4.21.3
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- Pytorch 1.12.0
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- Datasets 1.14.0
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- Tokenizers 0.12.1
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VALID_shona_sna_audio_data.csv
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audio_path,transcript,lang,lang_code,gender,age,country,accent
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AUDIO_HOMEPATH/data/R6W5zU8ezS1V76stFCCwXZPPbwxhltrJ/audio.wav,0,shona,sna,Male,34.0,Australia,Shona
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AUDIO_HOMEPATH/data/8wO2rBjlXFkaBU11BhFXZ8JEgTIY0USA/audio.wav,4,shona,sna,Male,23.0,Zimbabwe,
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AUDIO_HOMEPATH/data/3Ojig6rJkV2UvnRrqCpF8CWxQUaVlojm/audio.wav,2,shona,sna,Male,34.0,Australia,Shona
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AUDIO_HOMEPATH/data/ImBUzQW22uPvBx46BR3gkc6iqC7NzRvw/audio.wav,5,shona,sna,Male,34.0,Australia,Shona
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AUDIO_HOMEPATH/data/vudM0Q3QhYQRUSxnWwZLQJPFSpL1S9rk/audio.wav,7,shona,sna,Male,34.0,Australia,Shona
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AUDIO_HOMEPATH/data/M2G2KFjKpMSEvijN6txPxeDm4UlkbMqr/audio.wav,2,shona,sna,Male,23.0,Zimbabwe,
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afrospeech-wav2vec-sna_METRICS_VALID.json
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{"acc": 1.0, "f1": 1.0}
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afrospeech-wav2vec-sna_confusion_matrix_VALID.png
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digits-bar-plot-for-afrospeech-wav2vec-sna.png
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