w2v2-bert-r-Wolof-5-hours-kallaama-dataset
This model is a fine-tuned version of facebook/w2v-bert-2.0 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3781
- Wer: 0.5466
- Cer: 0.2727
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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 |
|---|---|---|---|---|---|
| 2.299 | 5.9480 | 400 | 1.9903 | 0.8333 | 0.4075 |
| 1.721 | 11.8959 | 800 | 1.7083 | 0.7612 | 0.4171 |
| 1.3926 | 17.8439 | 1200 | 1.6886 | 0.6504 | 0.3240 |
| 1.1457 | 23.7918 | 1600 | 1.5706 | 0.6120 | 0.3168 |
| 0.9292 | 29.7398 | 2000 | 1.7518 | 0.5761 | 0.2857 |
| 0.7281 | 35.6877 | 2400 | 1.8207 | 0.5500 | 0.2746 |
| 0.5193 | 41.6357 | 2800 | 1.8834 | 0.5599 | 0.2794 |
| 0.3446 | 47.5836 | 3200 | 2.3781 | 0.5466 | 0.2727 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.1.0+cu118
- Datasets 2.17.0
- Tokenizers 0.19.1
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Base model
facebook/w2v-bert-2.0