---
license: mit
base_model: Davlan/afro-xlmr-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: angela_untranslated_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_untranslated_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: 0.5952
- Precision: 0.3916
- Recall: 0.1193
- F1: 0.1829
- Accuracy: 0.8778

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1532        | 1.0   | 1283 | 0.3419          | 0.3699    | 0.0649 | 0.1105 | 0.8780   |
| 0.1318        | 2.0   | 2566 | 0.3842          | 0.3875    | 0.0632 | 0.1087 | 0.8785   |
| 0.1097        | 3.0   | 3849 | 0.4611          | 0.4008    | 0.1028 | 0.1637 | 0.8786   |
| 0.09          | 4.0   | 5132 | 0.5673          | 0.4044    | 0.1059 | 0.1679 | 0.8788   |
| 0.0731        | 5.0   | 6415 | 0.5952          | 0.3916    | 0.1193 | 0.1829 | 0.8778   |


### Framework versions

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