Model save

README.md

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+---
+base_model: aubmindlab/bert-base-arabertv02
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: 11levels_26977
+  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. -->
+
+# 11levels_26977
+
+This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2826
+- Macro F1: 0.5615
+- Macro Precision: 0.5598
+- Macro Recall: 0.5707
+- Accuracy: 0.6702
+
+## 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: 64
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro Precision | Macro Recall | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|
+| No log        | 1.0   | 422  | 1.0239          | 0.5139   | 0.5318          | 0.5450       | 0.6583   |
+| 1.2083        | 2.0   | 844  | 0.9638          | 0.5598   | 0.5557          | 0.5921       | 0.6787   |
+| 0.8027        | 3.0   | 1266 | 0.9719          | 0.5608   | 0.5761          | 0.5539       | 0.6833   |
+| 0.5643        | 4.0   | 1688 | 1.1153          | 0.5600   | 0.5591          | 0.5718       | 0.6714   |
+| 0.3806        | 5.0   | 2110 | 1.2091          | 0.5698   | 0.5705          | 0.5789       | 0.6712   |
+| 0.2509        | 6.0   | 2532 | 1.2826          | 0.5615   | 0.5598          | 0.5707       | 0.6702   |
+
+
+### Framework versions
+
+- Transformers 4.43.4
+- Pytorch 2.6.0+cu124
+- Datasets 3.4.1
+- Tokenizers 0.19.1

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