Best fold: (F1=0.8602)

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: Twitter_concatenatewithPrompt_Augmentation-fold4
+  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. -->
+
+# Twitter_concatenatewithPrompt_Augmentation-fold4
+
+This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-base-arabertv02-twitter) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4110
+- Accuracy: 0.8605
+- Macro F1: 0.8602
+- Weighted F1: 0.8606
+- F1 Pro: 0.8789
+- F1 Against: 0.856
+- F1 Neutral: 0.8458
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.1
+- num_epochs: 8
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Macro F1 | Weighted F1 | F1 Pro | F1 Against | F1 Neutral |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|:------:|:----------:|:----------:|
+| 1.7120        | 2.3294 | 100  | 0.5647          | 0.7656   | 0.7664   | 0.7661      | 0.7867 | 0.7479     | 0.7644     |
+| 0.8256        | 4.6588 | 200  | 0.4331          | 0.8427   | 0.8422   | 0.8427      | 0.8610 | 0.8392     | 0.8265     |
+| 0.4433        | 6.9882 | 300  | 0.4109          | 0.8605   | 0.8602   | 0.8606      | 0.8789 | 0.856      | 0.8458     |
+
+
+### Framework versions
+
+- Transformers 5.0.0
+- Pytorch 2.9.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.22.2

model.safetensors

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 version https://git-lfs.github.com/spec/v1
-oid sha256:4410d4f743ac07a56db8057ffcdf0cf8eb776efde990f3f6ae5299ecdcbdf76e
+oid sha256:a35ae24084973080dad80a806c8f8038a7e52edb08d3c86f6095fcc45ffa5c6b
 size 540806124

tokenizer_config.json

@@ -0,0 +1,23 @@
+{
+  "backend": "tokenizers",
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": false,
+  "from_slow": true,
+  "is_local": false,
+  "mask_token": "[MASK]",
+  "max_len": 512,
+  "model_max_length": 512,
+  "never_split": [
+    "[بريد]",
+    "[مستخدم]",
+    "[رابط]"
+  ],
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]",
+  "use_fast": true
+}