---
license: mit
base_model: Davlan/afro-xlmr-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: angela_shuffle_punc_eval
  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_punc_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: 0.2116
- Precision: 0.3859
- Recall: 0.3254
- F1: 0.3531
- Accuracy: 0.9334

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1711        | 1.0   | 1283 | 0.1840          | 0.3850    | 0.1896 | 0.2540 | 0.9369   |
| 0.1439        | 2.0   | 2566 | 0.1923          | 0.3887    | 0.2629 | 0.3137 | 0.9331   |
| 0.1248        | 3.0   | 3849 | 0.2008          | 0.4106    | 0.2615 | 0.3195 | 0.9373   |
| 0.1076        | 4.0   | 5132 | 0.2012          | 0.3800    | 0.3472 | 0.3628 | 0.9318   |
| 0.089         | 5.0   | 6415 | 0.2116          | 0.3859    | 0.3254 | 0.3531 | 0.9334   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3