---
license: mit
base_model: Davlan/afro-xlmr-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: angela_diacritics_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_diacritics_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: 0.2180
- Precision: 0.3758
- Recall: 0.2049
- F1: 0.2652
- Accuracy: 0.9384

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2306        | 1.0   | 1283 | 0.1942          | 0.3818    | 0.0809 | 0.1335 | 0.9412   |
| 0.2083        | 2.0   | 2566 | 0.1989          | 0.4041    | 0.0909 | 0.1485 | 0.9419   |
| 0.1903        | 3.0   | 3849 | 0.1960          | 0.4151    | 0.1530 | 0.2236 | 0.9420   |
| 0.1696        | 4.0   | 5132 | 0.2051          | 0.3738    | 0.2140 | 0.2722 | 0.9383   |
| 0.1454        | 5.0   | 6415 | 0.2180          | 0.3758    | 0.2049 | 0.2652 | 0.9384   |


### Framework versions

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