---
license: mit
base_model: Davlan/afro-xlmr-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: three_class_5e-5_hausa
  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. -->

# three_class_5e-5_hausa

This model is a fine-tuned version of [Davlan/afro-xlmr-base](https://huggingface.co/Davlan/afro-xlmr-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2379
- Precision: 0.2316
- Recall: 0.1636
- F1: 0.1917
- Accuracy: 0.9392

## 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: 5e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2129        | 1.0   | 1283 | 0.2033          | 0.2278    | 0.0810 | 0.1195 | 0.9416   |
| 0.1901        | 2.0   | 2566 | 0.1988          | 0.2444    | 0.0890 | 0.1305 | 0.9429   |
| 0.1657        | 3.0   | 3849 | 0.2056          | 0.2561    | 0.1278 | 0.1705 | 0.9430   |
| 0.139         | 4.0   | 5132 | 0.2205          | 0.2269    | 0.1655 | 0.1914 | 0.9388   |
| 0.1179        | 5.0   | 6415 | 0.2379          | 0.2316    | 0.1636 | 0.1917 | 0.9392   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.1
- Tokenizers 0.13.3