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delete_only_filtering_hausa_v2
This model is a fine-tuned version of Davlan/afro-xlmr-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1645
- Precision: 0.34
- Recall: 0.3068
- F1: 0.3225
- Accuracy: 0.9505
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1903 | 1.0 | 932 | 0.1400 | 0.4212 | 0.1805 | 0.2527 | 0.9584 |
| 0.1566 | 2.0 | 1864 | 0.1343 | 0.4194 | 0.2202 | 0.2887 | 0.9582 |
| 0.1361 | 3.0 | 2796 | 0.1450 | 0.3347 | 0.3007 | 0.3168 | 0.9500 |
| 0.1092 | 4.0 | 3728 | 0.1519 | 0.3581 | 0.2935 | 0.3226 | 0.9525 |
| 0.0886 | 5.0 | 4660 | 0.1645 | 0.34 | 0.3068 | 0.3225 | 0.9505 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3
