---
license: mit
base_model: Davlan/afro-xlmr-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: only_english
  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. -->

# only_english

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: 0.1647
- Precision: 0.6988
- Recall: 0.5376
- F1: 0.6077
- Accuracy: 0.9561

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1733        | 1.0   | 1312 | 0.1466          | 0.684     | 0.4374 | 0.5336 | 0.9514   |
| 0.1394        | 2.0   | 2624 | 0.1439          | 0.7089    | 0.4819 | 0.5737 | 0.9546   |
| 0.1123        | 3.0   | 3936 | 0.1417          | 0.6983    | 0.5299 | 0.6026 | 0.9556   |
| 0.0899        | 4.0   | 5248 | 0.1522          | 0.7075    | 0.5303 | 0.6062 | 0.9563   |
| 0.0744        | 5.0   | 6560 | 0.1647          | 0.6988    | 0.5376 | 0.6077 | 0.9561   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3