---
license: mit
base_model: Davlan/afro-xlmr-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: angela_punc_untranslated_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_punc_untranslated_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: 0.1902
- Precision: 0.3889
- Recall: 0.2568
- F1: 0.3093
- Accuracy: 0.9517

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1524        | 1.0   | 1283 | 0.1547          | 0.4163    | 0.1471 | 0.2174 | 0.9546   |
| 0.1295        | 2.0   | 2566 | 0.1518          | 0.4489    | 0.1943 | 0.2712 | 0.9556   |
| 0.1113        | 3.0   | 3849 | 0.1614          | 0.4152    | 0.2323 | 0.2979 | 0.9538   |
| 0.0896        | 4.0   | 5132 | 0.1784          | 0.4248    | 0.2346 | 0.3023 | 0.9542   |
| 0.073         | 5.0   | 6415 | 0.1902          | 0.3889    | 0.2568 | 0.3093 | 0.9517   |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3