---
license: mit
base_model: Davlan/afro-xlmr-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: flipped_2e-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. -->

# flipped_2e-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: 0.1898
- Precision: 0.4205
- Recall: 0.2644
- F1: 0.3247
- Accuracy: 0.9417

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1886        | 1.0   | 1283 | 0.1796          | 0.3923    | 0.1576 | 0.2248 | 0.9419   |
| 0.1712        | 2.0   | 2566 | 0.1748          | 0.4347    | 0.2002 | 0.2741 | 0.9436   |
| 0.157         | 3.0   | 3849 | 0.1785          | 0.4346    | 0.2393 | 0.3086 | 0.9432   |
| 0.1439        | 4.0   | 5132 | 0.1838          | 0.4246    | 0.2604 | 0.3228 | 0.9422   |
| 0.1323        | 5.0   | 6415 | 0.1898          | 0.4205    | 0.2644 | 0.3247 | 0.9417   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3