---
license: mit
tags:
- automatic-speech-recognition
- asr
- pytorch
- wav2vec2
- wolof
- wo
model-index:
- name: wav2vec2-xls-r-300m-wolof
  results:
  - task: 
      name: Speech Recognition
      type: automatic-speech-recognition
 
    metrics:
       - name: Test WER
         type: wer
         value: 21.25
       - name: Validation Loss
         type: Loss
         value: 0.36

---
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# wav2vec2-xls-r-300m-wolof  

Wolof is a language spoken in Senegal and neighbouring countries, this language is not too well represented, there are few resources in the field of Text en speech
In this sense we aim to bring our contribution to this, it is in this sense that enters this repo. 

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) , that is trained with the largest available speech dataset of the  [ALFFA_PUBLIC project](https://github.com/besacier/ALFFA_PUBLIC/tree/master/ASR/WOLOF)

It achieves the following results on the evaluation set:
- Loss: 0.367826	
- Wer: 0.212565

## Model description
The duration of the training data is 16.8 hours, which we have divided into 10,000 audio files for the training and 3,339 for the test.
## Training and evaluation data
We eval the model at every 1500 step , and log it .  and save at every 33340 step
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-4
- train_batch_size: 3
- eval_batch_size : 8
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10.0

### Training results

| Step    | Training Loss | Validation Loss | Wer    |
|:-------:|:-------------:|:---------------:|:------:|
| 1500	 | 2.854200	 |0.642243	 |0.543964  |
| 3000	| 0.599200 |  0.468138 |  	0.429549|
| 4500	| 0.468300 |	0.433436 |	0.405644|
| 6000	| 0.427000 |	0.384873 |	0.344150|
| 7500	| 0.377000 |	0.374003 |	0.323892|
| 9000	| 0.337000 |	0.363674 |	0.306189|
| 10500	| 0.302400	| 0.349884	 |0 .283908 |
| 12000	| 0.264100	| 0.344104  |0.277120|
| 13500	|0 .254000	|0.341820	 |0.271316|
| 15000 |	0.208400|	0.326502 |	0.260695|
| 16500 |	0.203500|	0.326209 |	0.250313|
| 18000	|0.159800	|0.323539 |	0.239851|
| 19500 |	0.158200 |	0.310694 |	0.230028|
| 21000 |	0.132800 |	0.338318 |	0.229283|
| 22500 |	0.112800 |	0.336765 |	0.224145|
| 24000 |	0.103600 |	0.350208 |	0.227073 |
| 25500 |	0.091400 |	0.353609 |	0.221589 |
| 27000 | 0.084400 |	0.367826 |	0.212565 |


### Framework versions
- Transformers 4.11
- Pytorch 1.10.0
- Datasets 1.13