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

# angela_shuffle_test

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: 0.1672
- Precision: 0.6214
- Recall: 0.4942
- F1: 0.5505
- Accuracy: 0.9504

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1882        | 1.0   | 1283 | 0.1566          | 0.6823    | 0.4277 | 0.5258 | 0.9518   |
| 0.1551        | 2.0   | 2566 | 0.1507          | 0.6940    | 0.4451 | 0.5423 | 0.9533   |
| 0.1385        | 3.0   | 3849 | 0.1545          | 0.6903    | 0.4503 | 0.5450 | 0.9532   |
| 0.1163        | 4.0   | 5132 | 0.1610          | 0.6288    | 0.4943 | 0.5535 | 0.9507   |
| 0.0994        | 5.0   | 6415 | 0.1672          | 0.6214    | 0.4942 | 0.5505 | 0.9504   |


### Framework versions

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