---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: afro-xlmr-base-hausa-seed-30
  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. -->

# afro-xlmr-base-hausa-seed-30

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: 0.1635
- Precision: 0.7407
- Recall: 0.5630
- F1: 0.6398
- Accuracy: 0.9599

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1599        | 1.0   | 1312 | 0.1431          | 0.7178    | 0.4516 | 0.5544 | 0.9536   |
| 0.1198        | 2.0   | 2624 | 0.1364          | 0.7155    | 0.5470 | 0.6200 | 0.9581   |
| 0.0932        | 3.0   | 3936 | 0.1381          | 0.7165    | 0.5708 | 0.6354 | 0.9588   |
| 0.0705        | 4.0   | 5248 | 0.1564          | 0.7529    | 0.5461 | 0.6330 | 0.9600   |
| 0.0559        | 5.0   | 6560 | 0.1635          | 0.7407    | 0.5630 | 0.6398 | 0.9599   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3