metadata
library_name: transformers
license: mit
base_model: castorini/afriberta_large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: results
results: []
results
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: 0.1577
- Accuracy: 0.9647
- F1: 0.9648
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 213 | 0.2605 | 0.9387 | 0.9385 |
| No log | 2.0 | 426 | 0.1656 | 0.9646 | 0.9645 |
| 0.4036 | 3.0 | 639 | 0.1491 | 0.9646 | 0.9644 |
| 0.4036 | 4.0 | 852 | 0.1510 | 0.9693 | 0.9691 |
| 0.0483 | 5.0 | 1065 | 0.1407 | 0.9693 | 0.9691 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0