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afriberta-small-finetuned-hausa
This model is a fine-tuned version of castorini/afriberta_small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1444
- Precision: 0.6873
- Recall: 0.4713
- F1: 0.5592
- Accuracy: 0.9618
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1493 | 1.0 | 2624 | 0.1382 | 0.6423 | 0.3968 | 0.4905 | 0.9572 |
| 0.1259 | 2.0 | 5248 | 0.1319 | 0.6734 | 0.4415 | 0.5333 | 0.9603 |
| 0.106 | 3.0 | 7872 | 0.1385 | 0.6908 | 0.4502 | 0.5452 | 0.9611 |
| 0.0949 | 4.0 | 10496 | 0.1377 | 0.6752 | 0.4759 | 0.5583 | 0.9613 |
| 0.086 | 5.0 | 13120 | 0.1444 | 0.6873 | 0.4713 | 0.5592 | 0.9618 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
