T2-usingF1

README.md

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+---
+library_name: transformers
+base_model: aubmindlab/bert-base-arabertv02-twitter
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: Model4_withclasess-arabertv2_base_T2_WS_A100v2_F1
+  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. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/so/Model4-with-add-clasess-T2-ArabertTv2-Bas-WS-A100/runs/ewc3vyii)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/so/Model4-with-add-clasess-T2-ArabertTv2-Bas-WS-A100/runs/ewc3vyii)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/so/Model4-with-add-clasess-T2-ArabertTv2-Bas-WS-A100/runs/ewc3vyii)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/so/Model4-with-add-clasess-T2-ArabertTv2-Bas-WS-A100/runs/ewc3vyii)
+# Model4_withclasess-arabertv2_base_T2_WS_A100v2_F1
+
+This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-base-arabertv02-twitter) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0813
+- F1-micro: 0.8359
+- Roc Auc: 0.9123
+- Accuracy: 0.7975
+
+## 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: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- 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: linear
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1-micro | Roc Auc | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------:|:--------:|
+| 0.0095        | 1.0   | 507  | 0.0767          | 0.8272   | 0.9095  | 0.7863   |
+| 0.0108        | 2.0   | 1014 | 0.0763          | 0.8237   | 0.9074  | 0.7842   |
+| 0.0108        | 3.0   | 1521 | 0.0749          | 0.8199   | 0.9029  | 0.7793   |
+| 0.0069        | 4.0   | 2028 | 0.0841          | 0.8299   | 0.9076  | 0.7961   |
+| 0.0057        | 5.0   | 2535 | 0.0835          | 0.8286   | 0.9105  | 0.7947   |
+| 0.0037        | 6.0   | 3042 | 0.0813          | 0.8359   | 0.9123  | 0.7975   |
+| 0.0029        | 7.0   | 3549 | 0.0875          | 0.8240   | 0.9081  | 0.7828   |
+| 0.0023        | 8.0   | 4056 | 0.0928          | 0.8334   | 0.9136  | 0.8010   |
+| 0.002         | 9.0   | 4563 | 0.0961          | 0.8159   | 0.9063  | 0.7730   |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.20.3

model.safetensors

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