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afriberta-finetuned-hausa
This model is a fine-tuned version of castorini/afriberta_large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1242
- Precision: 0.7104
- Recall: 0.5095
- F1: 0.5934
- Accuracy: 0.9647
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1369 | 1.0 | 2624 | 0.1256 | 0.6856 | 0.4541 | 0.5463 | 0.9614 |
| 0.1103 | 2.0 | 5248 | 0.1195 | 0.7014 | 0.4947 | 0.5802 | 0.9637 |
| 0.0868 | 3.0 | 7872 | 0.1242 | 0.7104 | 0.5095 | 0.5934 | 0.9647 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
