Wolof
Collection
Collection of Wav2Vec2-XLS-R, W2V2-BERT and Whisper models trained on ALFFA dataset
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Updated
wolof-1-hour-wav2vec2-xls-r-google-fleurs
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 3.0203
- Wer: 1.0
- Cer: 1.0
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 4.3753 | 25.0 | 200 | 3.0125 | 1.0 | 1.0 |
| 3.003 | 50.0 | 400 | 3.0203 | 1.0 | 1.0 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.1.0+cu118
- Datasets 2.17.0
- Tokenizers 0.19.1
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Model tree for asr-africa/wolof-1-hour-wav2vec2-xls-r-google-fleurs
Base model
facebook/wav2vec2-xls-r-300m