---
license: mit
base_model: Davlan/afro-xlmr-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: angela_shuffle_diacritics_regular_eval
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# angela_shuffle_diacritics_regular_eval

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: 0.1666
- Precision: 0.4058
- Recall: 0.2753
- F1: 0.3281
- Accuracy: 0.9565

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1497        | 1.0   | 1283 | 0.1387          | 0.4515    | 0.1507 | 0.2260 | 0.9593   |
| 0.1272        | 2.0   | 2566 | 0.1329          | 0.4710    | 0.2103 | 0.2908 | 0.9600   |
| 0.1092        | 3.0   | 3849 | 0.1442          | 0.4636    | 0.2263 | 0.3041 | 0.9598   |
| 0.0884        | 4.0   | 5132 | 0.1532          | 0.4088    | 0.2785 | 0.3313 | 0.9565   |
| 0.0708        | 5.0   | 6415 | 0.1666          | 0.4058    | 0.2753 | 0.3281 | 0.9565   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3