---
library_name: transformers
license: cc-by-4.0
base_model: Kuongan/BantuBERTa-vmw-finetuned
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: BantuBERTa-vmw-finetuned-vmw-noaug
  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. -->

# BantuBERTa-vmw-finetuned-vmw-noaug

This model is a fine-tuned version of [Kuongan/BantuBERTa-vmw-finetuned](https://huggingface.co/Kuongan/BantuBERTa-vmw-finetuned) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4673
- F1: 0.2169
- Roc Auc: 0.5714
- Accuracy: 0.4651

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.1056        | 1.0   | 49   | 0.3296          | 0.1466 | 0.5417  | 0.4729   |
| 0.1022        | 2.0   | 98   | 0.3384          | 0.1506 | 0.5425  | 0.4806   |
| 0.0889        | 3.0   | 147  | 0.3528          | 0.1372 | 0.5439  | 0.4651   |
| 0.071         | 4.0   | 196  | 0.3808          | 0.1874 | 0.5581  | 0.4264   |
| 0.0659        | 5.0   | 245  | 0.3800          | 0.1664 | 0.5478  | 0.4690   |
| 0.0534        | 6.0   | 294  | 0.3999          | 0.1873 | 0.5564  | 0.4651   |
| 0.0407        | 7.0   | 343  | 0.4108          | 0.1439 | 0.5378  | 0.4535   |
| 0.0368        | 8.0   | 392  | 0.4235          | 0.1970 | 0.5590  | 0.4612   |
| 0.0247        | 9.0   | 441  | 0.4248          | 0.1724 | 0.5497  | 0.4729   |
| 0.0213        | 10.0  | 490  | 0.4313          | 0.2049 | 0.5648  | 0.4690   |
| 0.0164        | 11.0  | 539  | 0.4384          | 0.1918 | 0.5592  | 0.4690   |
| 0.0144        | 12.0  | 588  | 0.4576          | 0.2116 | 0.5694  | 0.4574   |
| 0.0138        | 13.0  | 637  | 0.4575          | 0.2075 | 0.5665  | 0.4729   |
| 0.0117        | 14.0  | 686  | 0.4694          | 0.2008 | 0.5638  | 0.4574   |
| 0.0114        | 15.0  | 735  | 0.4673          | 0.2169 | 0.5714  | 0.4651   |
| 0.0098        | 16.0  | 784  | 0.4703          | 0.2034 | 0.5646  | 0.4690   |
| 0.0096        | 17.0  | 833  | 0.4729          | 0.1943 | 0.5600  | 0.4574   |
| 0.0102        | 18.0  | 882  | 0.4707          | 0.1989 | 0.5619  | 0.4690   |
| 0.0101        | 19.0  | 931  | 0.4720          | 0.1990 | 0.5622  | 0.4690   |


### Framework versions

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