| | --- |
| | license: mit |
| | base_model: castorini/afriberta_large |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | model-index: |
| | - name: afroBERTaphdmodel500mb |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # afroBERTaphdmodel500mb |
| |
|
| | This model is a fine-tuned version of [castorini/afriberta_large](https://huggingface.co/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 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.44.0 |
| | - Pytorch 2.2.0+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.19.1 |
| |
|
