update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: AraBERT_token_classification__AraEval24_merged_rassd_aratweets
+  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. -->
+
+# AraBERT_token_classification__AraEval24_merged_rassd_aratweets
+
+This model is a fine-tuned version of [aubmindlab/bert-base-arabert](https://huggingface.co/aubmindlab/bert-base-arabert) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8783
+- Precision: 0.0736
+- Recall: 0.0243
+- F1: 0.0365
+- Accuracy: 0.8564
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.7095        | 1.0   | 3105  | 0.8134          | 1.0       | 0.0001 | 0.0002 | 0.8633   |
+| 0.6521        | 2.0   | 6210  | 0.7728          | 0.1149    | 0.0021 | 0.0041 | 0.8631   |
+| 0.5857        | 3.0   | 9315  | 0.7770          | 0.0383    | 0.0009 | 0.0017 | 0.8632   |
+| 0.5233        | 4.0   | 12420 | 0.7929          | 0.0896    | 0.0100 | 0.0180 | 0.8624   |
+| 0.5096        | 5.0   | 15525 | 0.7911          | 0.0716    | 0.0108 | 0.0187 | 0.8617   |
+| 0.4685        | 6.0   | 18630 | 0.8200          | 0.0906    | 0.0144 | 0.0248 | 0.8618   |
+| 0.4393        | 7.0   | 21735 | 0.8399          | 0.0939    | 0.0160 | 0.0273 | 0.8618   |
+| 0.4204        | 8.0   | 24840 | 0.8361          | 0.0862    | 0.0230 | 0.0363 | 0.8590   |
+| 0.3872        | 9.0   | 27945 | 0.8706          | 0.0782    | 0.0251 | 0.0380 | 0.8567   |
+| 0.3569        | 10.0  | 31050 | 0.8783          | 0.0736    | 0.0243 | 0.0365 | 0.8564   |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 1.12.1
+- Datasets 2.13.2
+- Tokenizers 0.13.3