update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- accuracy
+model-index:
+- name: Is_there_relation
+  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. -->
+
+# Is_there_relation
+
+This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8855
+- Macro F1: 0.7979
+- Precision: 0.8002
+- Recall: 0.7995
+- Kappa: 0.5894
+- Accuracy: 0.7995
+
+## 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: 128
+- seed: 25
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Precision | Recall | Kappa  | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 218  | 0.5160          | 0.7251   | 0.7659    | 0.7398 | 0.4511 | 0.7398   |
+| No log        | 2.0   | 437  | 0.4608          | 0.8014   | 0.8108    | 0.8049 | 0.5970 | 0.8049   |
+| 0.4812        | 3.0   | 655  | 0.5087          | 0.7864   | 0.7900    | 0.7886 | 0.5661 | 0.7886   |
+| 0.4812        | 4.0   | 874  | 0.5219          | 0.8107   | 0.8118    | 0.8103 | 0.6177 | 0.8103   |
+| 0.2407        | 5.0   | 1092 | 0.5657          | 0.8319   | 0.8416    | 0.8347 | 0.6588 | 0.8347   |
+| 0.2407        | 6.0   | 1311 | 0.6980          | 0.7988   | 0.8074    | 0.8022 | 0.5917 | 0.8022   |
+| 0.1383        | 7.0   | 1529 | 0.7769          | 0.7933   | 0.8017    | 0.7967 | 0.5805 | 0.7967   |
+| 0.1383        | 8.0   | 1748 | 0.7336          | 0.8059   | 0.8087    | 0.8076 | 0.6058 | 0.8076   |
+| 0.1383        | 9.0   | 1966 | 0.7426          | 0.7988   | 0.8074    | 0.8022 | 0.5917 | 0.8022   |
+| 0.0878        | 10.0  | 2185 | 0.8211          | 0.8017   | 0.8098    | 0.8049 | 0.5975 | 0.8049   |
+| 0.0878        | 11.0  | 2403 | 0.8737          | 0.7955   | 0.7969    | 0.7967 | 0.5846 | 0.7967   |
+| 0.0573        | 12.0  | 2622 | 0.9043          | 0.7900   | 0.7914    | 0.7913 | 0.5735 | 0.7913   |
+| 0.0573        | 13.0  | 2840 | 0.8937          | 0.7906   | 0.7909    | 0.7913 | 0.5751 | 0.7913   |
+| 0.0423        | 14.0  | 3059 | 0.9004          | 0.8013   | 0.8019    | 0.8022 | 0.5967 | 0.8022   |
+| 0.0423        | 14.97 | 3270 | 0.8855          | 0.7979   | 0.8002    | 0.7995 | 0.5894 | 0.7995   |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.0.1+cu118
+- Tokenizers 0.13.3