Model reference · open weights

whisper-small-wolof

Available as managed deployment Audio M9and2M · community Speech→text 1 variants 537 dl/mo

whisper-small-wolof is an open-weight audio or speech model from M9and2M. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.

Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.

What it is

Released byM9and2M
TypeAudio & music
TaskSpeech→text
Parameters (lead)242M
Runs withtransformers
Released2024-06-27
Popularity537 downloads / month
LicenceOpen weights

About

What whisper-small-wolof is

Model Overview

This repository hosts an Automatic Speech Recognition (ASR) model for the Wolof language, fine-tuned from OpenAI's Whisper-small model. This model aims to provide accurate transcription of Wolof audio data.

Model Details

  • Model Base: Whisper-small
  • Loss: 0.123
  • WER: 0.17

Dataset

The dataset used for training and evaluating this model is a collection from various sources, ensuring a rich and diverse set of Wolof audio samples. The collection is available in my Hugging Face account is used by keeping only the audios with duration shorter than 6 second.

Read the full model card
  • Training Dataset: 57 hours
  • Test Dataset: 10 hours

For detailed information about the dataset, please refer to the M9and2M/Wolof_ASR_dataset.

Training

The training process was adapted from the code in the Finetune Wa2vec 2.0 For Speech Recognition written to fine-tune Wav2Vec2.0 for speech recognition. Special thanks to the author, Duy Khanh, Le for providing a robust and flexible training framework.

The model was trained with the following configuration:

  • Seed: 19
  • Training Batch Size: 1
  • Gradient Accumulation Steps: 8
  • Number of GPUs: 2

Optimizer : AdamW

  • Learning Rate: 1e-7

Scheduler: OneCycleLR

  • Max Learning Rate: 5e-5

Acknowledgements

This model was built using OpenAI's Whisper-small architecture and fine-tuned with a dataset collected from various sources. Special thanks to the creators and contributors of the dataset.

More Information

This model has been developed in the context of my Master Thesis at ETSIT-UPM, Madrid under the supervision of Prof. Luis A. Hernández Gómez.

Contact

For any inquiries or questions, please contact mamadou.marone@ensea.fr

From the published model card. Full card on the HuggingFace links in the sidebar.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys whisper-small-wolof for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (whisper-small-wolof below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/audio/transcriptions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -F model="whisper-small-wolof" -F file=@audio.mp3

Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.

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