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README.md
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---
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library_name: transformers
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license: cc-by-4.0
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base_model: dsfsi/BantuBERTa
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tags:
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- generated_from_trainer
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metrics:
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- f1
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- accuracy
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model-index:
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- name: BantuBERTa-vmw-noaug
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# BantuBERTa-vmw-noaug
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This model is a fine-tuned version of [dsfsi/BantuBERTa](https://huggingface.co/dsfsi/BantuBERTa) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2888
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- F1: 0.0
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- Roc Auc: 0.5
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- Accuracy: 0.4612
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 100
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- num_epochs: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---:|:-------:|:--------:|
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| 0.586 | 1.0 | 49 | 0.4098 | 0.0 | 0.4989 | 0.4574 |
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| 0.3154 | 2.0 | 98 | 0.2930 | 0.0 | 0.5 | 0.4612 |
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| 0.2897 | 3.0 | 147 | 0.2906 | 0.0 | 0.5 | 0.4612 |
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| 0.2895 | 4.0 | 196 | 0.2892 | 0.0 | 0.5 | 0.4612 |
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| 0.285 | 5.0 | 245 | 0.2888 | 0.0 | 0.5 | 0.4612 |
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### Framework versions
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- Transformers 4.47.0
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- Pytorch 2.5.1+cu121
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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model.safetensors
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