---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: luganda-ner-v6
  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. -->

# luganda-ner-v6

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2031
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9713

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| 0.2234        | 1.0   | 618  | 0.2186          | 0.0       | 0.0    | 0.0 | 0.9498   |
| 0.0884        | 2.0   | 1236 | 0.1490          | 0.0       | 0.0    | 0.0 | 0.9609   |
| 0.0686        | 3.0   | 1854 | 0.1606          | 0.0       | 0.0    | 0.0 | 0.9617   |
| 0.0484        | 4.0   | 2472 | 0.1728          | 0.0       | 0.0    | 0.0 | 0.9639   |
| 0.0233        | 5.0   | 3090 | 0.1682          | 0.0       | 0.0    | 0.0 | 0.9658   |
| 0.0196        | 6.0   | 3708 | 0.1738          | 0.0       | 0.0    | 0.0 | 0.9702   |
| 0.0135        | 7.0   | 4326 | 0.1744          | 0.0       | 0.0    | 0.0 | 0.9701   |
| 0.0122        | 8.0   | 4944 | 0.1979          | 0.0       | 0.0    | 0.0 | 0.9699   |
| 0.0062        | 9.0   | 5562 | 0.1992          | 0.0       | 0.0    | 0.0 | 0.9708   |
| 0.0047        | 10.0  | 6180 | 0.2031          | 0.0       | 0.0    | 0.0 | 0.9713   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1