---
library_name: transformers
license: mit
base_model: Kuongan/afro-xlmr-base-sun-noaug
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: CS221-afro-xlmr-base-sun-noaug-finetuned-sun-tapt
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# CS221-afro-xlmr-base-sun-noaug-finetuned-sun-tapt

This model is a fine-tuned version of [Kuongan/afro-xlmr-base-sun-noaug](https://huggingface.co/Kuongan/afro-xlmr-base-sun-noaug) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1742
- F1: 0.5195
- Roc Auc: 0.7121
- Accuracy: 0.7537

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.1957        | 1.0   | 52   | 0.1748          | 0.3924 | 0.6586  | 0.7854   |
| 0.2027        | 2.0   | 104  | 0.1789          | 0.3654 | 0.6387  | 0.7634   |
| 0.1953        | 3.0   | 156  | 0.1768          | 0.4195 | 0.6657  | 0.7707   |
| 0.1685        | 4.0   | 208  | 0.1858          | 0.4239 | 0.6645  | 0.7512   |
| 0.164         | 5.0   | 260  | 0.1744          | 0.4035 | 0.6627  | 0.7659   |
| 0.1553        | 6.0   | 312  | 0.1762          | 0.4651 | 0.6905  | 0.7561   |
| 0.154         | 7.0   | 364  | 0.1725          | 0.5028 | 0.6999  | 0.7683   |
| 0.1293        | 8.0   | 416  | 0.1768          | 0.4513 | 0.6843  | 0.7707   |
| 0.1381        | 9.0   | 468  | 0.1742          | 0.5195 | 0.7121  | 0.7537   |
| 0.1212        | 10.0  | 520  | 0.2013          | 0.3664 | 0.6299  | 0.7439   |
| 0.0988        | 11.0  | 572  | 0.1723          | 0.4813 | 0.6954  | 0.7683   |
| 0.1053        | 12.0  | 624  | 0.1810          | 0.4360 | 0.6706  | 0.7780   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0