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---
library_name: transformers
license: cc-by-4.0
base_model: dsfsi/BantuBERTa
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: BantuBERTa-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-noaug
This model is a fine-tuned version of [dsfsi/BantuBERTa](https://huggingface.co/dsfsi/BantuBERTa) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4098
- F1: 0.0
- Roc Auc: 0.4989
- Accuracy: 0.4574
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---:|:-------:|:--------:|
| 0.586 | 1.0 | 49 | 0.4098 | 0.0 | 0.4989 | 0.4574 |
| 0.3154 | 2.0 | 98 | 0.2930 | 0.0 | 0.5 | 0.4612 |
| 0.2897 | 3.0 | 147 | 0.2906 | 0.0 | 0.5 | 0.4612 |
| 0.2895 | 4.0 | 196 | 0.2892 | 0.0 | 0.5 | 0.4612 |
| 0.285 | 5.0 | 245 | 0.2888 | 0.0 | 0.5 | 0.4612 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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