metadata
license: mit
base_model: castorini/afriberta_large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: afroBERTaphdmodel500mb
results: []
afroBERTaphdmodel500mb
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: 0.0
- Accuracy: 1.0
- F1: 1.0
- Precision: 1.0
- Recall: 1.0
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0 | 1.0 | 2125 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 2.0 | 4250 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 3.0 | 6375 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 4.0 | 8500 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1