Model save

README.md

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+---
+base_model: aubmindlab/bert-base-arabertv02
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: 2levels_52521
+  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. -->
+
+# 2levels_52521
+
+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: 0.9976
+- Macro F1: 0.8132
+- Macro Precision: 0.8220
+- Macro Recall: 0.8153
+- Accuracy: 0.8140
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|
+| 0.4301        | 1.0   | 821  | 0.3758          | 0.8300   | 0.8360          | 0.8315       | 0.8305   |
+| 0.2994        | 2.0   | 1642 | 0.4510          | 0.8141   | 0.8311          | 0.8175       | 0.8157   |
+| 0.2131        | 3.0   | 2463 | 0.5463          | 0.8077   | 0.8252          | 0.8113       | 0.8095   |
+| 0.0958        | 4.0   | 3284 | 0.7365          | 0.8081   | 0.8229          | 0.8113       | 0.8096   |
+| 0.055         | 5.0   | 4105 | 0.9349          | 0.8113   | 0.8245          | 0.8142       | 0.8126   |
+| 0.0352        | 6.0   | 4926 | 0.9976          | 0.8132   | 0.8220          | 0.8153       | 0.8140   |
+
+
+### Framework versions
+
+- Transformers 4.43.4
+- Pytorch 2.6.0+cu124
+- Datasets 3.4.1
+- Tokenizers 0.19.1

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