metadata
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
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 , that is trained with the largest available speech dataset of the ALFFA_PUBLIC project
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