Model save

README.md

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+---
+library_name: transformers
+license: cc-by-4.0
+base_model: Kuongan/BantuBERTa-vmw-noaug
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: CS221-BantuBERTa-vmw-noaug-finetuned-vmw-tapt
+  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. -->
+
+# CS221-BantuBERTa-vmw-noaug-finetuned-vmw-tapt
+
+This model is a fine-tuned version of [Kuongan/BantuBERTa-vmw-noaug](https://huggingface.co/Kuongan/BantuBERTa-vmw-noaug) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2417
+- F1: 0.0
+- Roc Auc: 0.5
+- Accuracy: 0.5977
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---:|:-------:|:--------:|
+| 0.2591        | 1.0   | 65   | 0.2460          | 0.0 | 0.5     | 0.5977   |
+| 0.2261        | 2.0   | 130  | 0.2439          | 0.0 | 0.5     | 0.5977   |
+| 0.2091        | 3.0   | 195  | 0.2425          | 0.0 | 0.5     | 0.5977   |
+| 0.2231        | 4.0   | 260  | 0.2417          | 0.0 | 0.5     | 0.5977   |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

model.safetensors

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