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

# 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: 0.1716
- Precision: 0.4009
- Recall: 0.2840
- F1: 0.3325
- Accuracy: 0.9559

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1421        | 1.0   | 1283 | 0.1347          | 0.4610    | 0.1779 | 0.2567 | 0.9594   |
| 0.1234        | 2.0   | 2566 | 0.1332          | 0.4847    | 0.1920 | 0.2750 | 0.9603   |
| 0.1041        | 3.0   | 3849 | 0.1412          | 0.4581    | 0.2305 | 0.3067 | 0.9595   |
| 0.0822        | 4.0   | 5132 | 0.1562          | 0.3979    | 0.2752 | 0.3253 | 0.9559   |
| 0.0664        | 5.0   | 6415 | 0.1716          | 0.4009    | 0.2840 | 0.3325 | 0.9559   |


### Framework versions

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