---
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    |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1