---
library_name: transformers
license: mit
base_model: Davlan/afro-xlmr-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: afro-xlmr-base-ptbr-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-ptbr-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: 0.5573
- F1: 0.6760
- Roc Auc: 0.8141
- Accuracy: 0.5860

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
| 0.2255        | 1.0   | 728   | 0.2284          | 0.6554 | 0.7738  | 0.6118   |
| 0.1591        | 2.0   | 1456  | 0.2288          | 0.6718 | 0.8000  | 0.6183   |
| 0.1038        | 3.0   | 2184  | 0.2640          | 0.6774 | 0.8045  | 0.6129   |
| 0.0506        | 4.0   | 2912  | 0.3305          | 0.6603 | 0.8168  | 0.5570   |
| 0.0459        | 5.0   | 3640  | 0.3809          | 0.6521 | 0.8088  | 0.5505   |
| 0.0222        | 6.0   | 4368  | 0.3868          | 0.6463 | 0.7892  | 0.5720   |
| 0.0179        | 7.0   | 5096  | 0.4026          | 0.6816 | 0.8139  | 0.6      |
| 0.0087        | 8.0   | 5824  | 0.4520          | 0.6694 | 0.8083  | 0.5871   |
| 0.0058        | 9.0   | 6552  | 0.4769          | 0.6703 | 0.8048  | 0.5882   |
| 0.0064        | 10.0  | 7280  | 0.4871          | 0.6841 | 0.8187  | 0.5946   |
| 0.0025        | 11.0  | 8008  | 0.5414          | 0.6611 | 0.8152  | 0.5688   |
| 0.0042        | 12.0  | 8736  | 0.5374          | 0.6778 | 0.8154  | 0.5925   |
| 0.0013        | 13.0  | 9464  | 0.5331          | 0.6744 | 0.8081  | 0.5968   |
| 0.0048        | 14.0  | 10192 | 0.5573          | 0.6760 | 0.8141  | 0.5860   |


### Framework versions

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