Model save

README.md

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+---
+library_name: transformers
+base_model: aubmindlab/bert-base-arabertv2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: bert-base-arabertv2_D3Lex_CE_19levels
+  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. -->
+
+# bert-base-arabertv2_D3Lex_CE_19levels
+
+This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.8342
+- Macro F1: 0.4364
+- Macro Precision: 0.4424
+- Macro Recall: 0.4454
+- Accuracy: 0.5140
+- Accuracy With Margin: 0.6744
+- Distance: 1.2527
+- Quadratic weighted kappa: 0.7889
+- Accuracy 7: 0.6179
+- Accuracy 5: 0.6653
+- Accuracy 3: 0.7363
+
+## 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
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Use OptimizerNames.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: 6
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro Precision | Macro Recall | Accuracy | Accuracy With Margin | Distance | Quadratic weighted kappa | Accuracy 7 | Accuracy 5 | Accuracy 3 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:--------------------:|:--------:|:------------------------:|:----------:|:----------:|:----------:|
+| 1.8254        | 1.0   | 857  | 1.4573          | 0.3478   | 0.3741          | 0.3804       | 0.5044   | 0.6513               | 1.3171   | 0.7790                   | 0.6223     | 0.6773     | 0.7415     |
+| 1.2699        | 2.0   | 1714 | 1.4409          | 0.4133   | 0.4330          | 0.4316       | 0.5157   | 0.6688               | 1.2666   | 0.7825                   | 0.6230     | 0.6802     | 0.7497     |
+| 1.0213        | 3.0   | 2571 | 1.4714          | 0.4157   | 0.4210          | 0.4276       | 0.5272   | 0.6711               | 1.2473   | 0.7889                   | 0.6308     | 0.6780     | 0.7458     |
+| 0.8308        | 4.0   | 3428 | 1.6169          | 0.4074   | 0.4422          | 0.4110       | 0.5171   | 0.6724               | 1.2573   | 0.7848                   | 0.6194     | 0.6663     | 0.7397     |
+| 0.6128        | 5.0   | 4285 | 1.7657          | 0.4222   | 0.4375          | 0.4349       | 0.5164   | 0.6737               | 1.2575   | 0.7861                   | 0.6208     | 0.6703     | 0.7391     |
+| 0.4786        | 6.0   | 5142 | 1.8342          | 0.4364   | 0.4424          | 0.4454       | 0.5140   | 0.6744               | 1.2527   | 0.7889                   | 0.6179     | 0.6653     | 0.7363     |
+
+
+### Framework versions
+
+- Transformers 4.53.2
+- Pytorch 2.6.0+cu124
+- Datasets 4.0.0
+- Tokenizers 0.21.2

all_results.json

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+{
+    "eval_Distance": 1.2666210670314637,
+    "eval_Quadratic Weighted Kappa": 0.7824598012075371,
+    "eval_accuracy": 0.5157318741450069,
+    "eval_accuracy_3": 0.7496580027359782,
+    "eval_accuracy_5": 0.6801641586867305,
+    "eval_accuracy_7": 0.6229822161422709,
+    "eval_accuracy_with_margin": 0.6688098495212038,
+    "eval_loss": 1.4409170150756836,
+    "eval_macro_f1": 0.4133400339951421,
+    "eval_macro_precision": 0.4329746157332755,
+    "eval_macro_recall": 0.4315951261744784,
+    "eval_runtime": 7.1213,
+    "eval_samples_per_second": 1026.494,
+    "eval_steps_per_second": 64.173,
+    "test_Distance": 1.2098545155091958,
+    "test_Quadratic Weighted Kappa": 0.7923845095768535,
+    "test_accuracy": 0.5168816909140818,
+    "test_accuracy_3": 0.7318144386494647,
+    "test_accuracy_5": 0.6690914081800714,
+    "test_accuracy_7": 0.6177600878396926,
+    "test_accuracy_with_margin": 0.6662091682679111,
+    "test_loss": 1.4232884645462036,
+    "test_macro_f1": 0.41679186365313936,
+    "test_macro_precision": 0.43817992671310624,
+    "test_macro_recall": 0.41739286889353727,
+    "test_runtime": 7.1992,
+    "test_samples_per_second": 1012.05,
+    "test_steps_per_second": 63.34
+}

eval_results.json

@@ -0,0 +1,16 @@
+{
+    "eval_Distance": 1.2666210670314637,
+    "eval_Quadratic Weighted Kappa": 0.7824598012075371,
+    "eval_accuracy": 0.5157318741450069,
+    "eval_accuracy_3": 0.7496580027359782,
+    "eval_accuracy_5": 0.6801641586867305,
+    "eval_accuracy_7": 0.6229822161422709,
+    "eval_accuracy_with_margin": 0.6688098495212038,
+    "eval_loss": 1.4409170150756836,
+    "eval_macro_f1": 0.4133400339951421,
+    "eval_macro_precision": 0.4329746157332755,
+    "eval_macro_recall": 0.4315951261744784,
+    "eval_runtime": 7.1213,
+    "eval_samples_per_second": 1026.494,
+    "eval_steps_per_second": 64.173
+}

model.safetensors

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 version https://git-lfs.github.com/spec/v1
-oid sha256:37caeff6f11e3e01fec5a3961e0d9f4dbef9555a990b2e546590a750890ed4cd
+oid sha256:41473b787b2d3870e9f7ac031ba14e26ab2a1c682f63d7eab8219de7b2534f29
 size 540855364

test_results.json

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+{
+    "test_Distance": 1.2098545155091958,
+    "test_Quadratic Weighted Kappa": 0.7923845095768535,
+    "test_accuracy": 0.5168816909140818,
+    "test_accuracy_3": 0.7318144386494647,
+    "test_accuracy_5": 0.6690914081800714,
+    "test_accuracy_7": 0.6177600878396926,
+    "test_accuracy_with_margin": 0.6662091682679111,
+    "test_loss": 1.4232884645462036,
+    "test_macro_f1": 0.41679186365313936,
+    "test_macro_precision": 0.43817992671310624,
+    "test_macro_recall": 0.41739286889353727,
+    "test_runtime": 7.1992,
+    "test_samples_per_second": 1012.05,
+    "test_steps_per_second": 63.34
+}