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BantuBERTa-vmw-finetuned

Text Classification
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roberta
Generated from Trainer
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README.md ADDED
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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-finetuned
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+ results: []
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+ ---
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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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+
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+ # BantuBERTa-vmw-finetuned
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+
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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: 0.3399
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+ - F1: 0.1513
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+ - Roc Auc: 0.5440
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+ - Accuracy: 0.4574
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | 0.4095 | 1.0 | 66 | 0.3112 | 0.0 | 0.5 | 0.4612 |
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+ | 0.2908 | 2.0 | 132 | 0.2903 | 0.0 | 0.5 | 0.4612 |
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+ | 0.284 | 3.0 | 198 | 0.2882 | 0.0 | 0.5 | 0.4612 |
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+ | 0.2958 | 4.0 | 264 | 0.2879 | 0.0 | 0.5 | 0.4612 |
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+ | 0.2749 | 5.0 | 330 | 0.2851 | 0.0139 | 0.5033 | 0.4651 |
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+ | 0.265 | 6.0 | 396 | 0.2868 | 0.0574 | 0.5173 | 0.4729 |
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+ | 0.2281 | 7.0 | 462 | 0.2802 | 0.1073 | 0.5338 | 0.4845 |
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+ | 0.1963 | 8.0 | 528 | 0.2876 | 0.1109 | 0.5353 | 0.4651 |
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+ | 0.1749 | 9.0 | 594 | 0.3040 | 0.0966 | 0.5282 | 0.4496 |
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+ | 0.1534 | 10.0 | 660 | 0.3046 | 0.1322 | 0.5396 | 0.4612 |
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+ | 0.1336 | 11.0 | 726 | 0.3129 | 0.1602 | 0.5473 | 0.4690 |
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+ | 0.1194 | 12.0 | 792 | 0.3222 | 0.1287 | 0.5372 | 0.4612 |
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+ | 0.1106 | 13.0 | 858 | 0.3269 | 0.1633 | 0.5507 | 0.4729 |
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+ | 0.1004 | 14.0 | 924 | 0.3296 | 0.1269 | 0.5360 | 0.4496 |
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+ | 0.091 | 15.0 | 990 | 0.3364 | 0.1612 | 0.5513 | 0.4690 |
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+ | 0.0855 | 16.0 | 1056 | 0.3347 | 0.1570 | 0.5472 | 0.4690 |
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+ | 0.079 | 17.0 | 1122 | 0.3399 | 0.1513 | 0.5440 | 0.4574 |
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+
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+
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+ ### Framework versions
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+
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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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