---
library_name: transformers
license: mit
base_model: Davlan/afro-xlmr-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: afro-xlmr-base-tat-MICRO
  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. -->

# afro-xlmr-base-tat-MICRO

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: 0.3352
- F1: 0.7041
- Roc Auc: 0.8304
- Accuracy: 0.6909

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.2295        | 1.0   | 345  | 0.2586          | 0.5653 | 0.7200  | 0.5818   |
| 0.174         | 2.0   | 690  | 0.2525          | 0.6211 | 0.7728  | 0.6295   |
| 0.1379        | 3.0   | 1035 | 0.2428          | 0.6566 | 0.7980  | 0.6477   |
| 0.0958        | 4.0   | 1380 | 0.2517          | 0.6689 | 0.7849  | 0.6636   |
| 0.0594        | 5.0   | 1725 | 0.2693          | 0.6667 | 0.8033  | 0.65     |
| 0.0605        | 6.0   | 2070 | 0.3010          | 0.6637 | 0.8047  | 0.6545   |
| 0.0325        | 7.0   | 2415 | 0.3619          | 0.6569 | 0.8053  | 0.6545   |
| 0.0141        | 8.0   | 2760 | 0.3174          | 0.6944 | 0.8326  | 0.6727   |
| 0.03          | 9.0   | 3105 | 0.3352          | 0.7041 | 0.8304  | 0.6909   |
| 0.0101        | 10.0  | 3450 | 0.3533          | 0.6766 | 0.8117  | 0.6682   |
| 0.0054        | 11.0  | 3795 | 0.3688          | 0.6950 | 0.8274  | 0.6795   |
| 0.007         | 12.0  | 4140 | 0.3798          | 0.6983 | 0.8345  | 0.675    |
| 0.0075        | 13.0  | 4485 | 0.4220          | 0.6791 | 0.8228  | 0.6614   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0