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

# no_repeats

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: 0.1658
- Precision: 0.7350
- Recall: 0.5701
- F1: 0.6421
- Accuracy: 0.9596

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1578        | 1.0   | 1283 | 0.1410          | 0.7141    | 0.4748 | 0.5704 | 0.9540   |
| 0.1189        | 2.0   | 2566 | 0.1336          | 0.7023    | 0.5501 | 0.6170 | 0.9568   |
| 0.0929        | 3.0   | 3849 | 0.1406          | 0.7380    | 0.5433 | 0.6259 | 0.9584   |
| 0.0725        | 4.0   | 5132 | 0.1512          | 0.7283    | 0.5751 | 0.6427 | 0.9591   |
| 0.057         | 5.0   | 6415 | 0.1658          | 0.7350    | 0.5701 | 0.6421 | 0.9596   |


### Framework versions

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