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afriberta-large-finetuned-hausa-2e-3
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: 0.2359
- Precision: 0.1719
- Recall: 0.0276
- F1: 0.0476
- Accuracy: 0.9373
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: 0.002
- 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 |
|---|---|---|---|---|---|---|---|
| 0.2428 | 1.0 | 1312 | 0.2358 | 0.1719 | 0.0276 | 0.0476 | 0.9373 |
| 0.2436 | 2.0 | 2624 | 0.2366 | 0.1719 | 0.0276 | 0.0476 | 0.9373 |
| 0.2429 | 3.0 | 3936 | 0.2365 | 0.1719 | 0.0276 | 0.0476 | 0.9373 |
| 0.2434 | 4.0 | 5248 | 0.2358 | 0.1719 | 0.0276 | 0.0476 | 0.9373 |
| 0.2411 | 5.0 | 6560 | 0.2359 | 0.1719 | 0.0276 | 0.0476 | 0.9373 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
