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

# redo_no_delete_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: 0.1749
- Precision: 0.3010
- Recall: 0.3389
- F1: 0.3188
- Accuracy: 0.9440

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2212        | 1.0   | 729  | 0.1391          | 0.3898    | 0.2023 | 0.2663 | 0.9572   |
| 0.1928        | 2.0   | 1458 | 0.1436          | 0.3436    | 0.3058 | 0.3236 | 0.9513   |
| 0.1517        | 3.0   | 2187 | 0.1498          | 0.3233    | 0.3384 | 0.3307 | 0.9473   |
| 0.1363        | 4.0   | 2916 | 0.1655          | 0.3095    | 0.3353 | 0.3219 | 0.9459   |
| 0.1039        | 5.0   | 3645 | 0.1749          | 0.3010    | 0.3389 | 0.3188 | 0.9440   |


### Framework versions

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