w2v2-bert-Wolof-1-hour-alffa-plus-fleurs-dataset
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 2.3087
- Wer: 0.5854
- Cer: 0.2091
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 |
|---|---|---|---|---|---|
| 1.2876 | 12.1212 | 200 | 1.1461 | 0.6952 | 0.2512 |
| 0.2576 | 24.2424 | 400 | 1.5723 | 0.6319 | 0.2207 |
| 0.0512 | 36.3636 | 600 | 1.9868 | 0.6052 | 0.2158 |
| 0.0046 | 48.4848 | 800 | 2.3087 | 0.5854 | 0.2091 |
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