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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: Type_of_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. -->
# Type_of_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: 1.3733
- Macro F1: 0.7820
- Precision: 0.7773
- Recall: 0.7917
- Kappa: 0.6875
- Accuracy: 0.7917
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:--------:|
| 1.1229 | 1.0 | 697 | 0.8030 | 0.7500 | 0.7330 | 0.7852 | 0.6631 | 0.7852 |
| 0.8056 | 2.0 | 1395 | 0.7428 | 0.7698 | 0.7571 | 0.7974 | 0.6888 | 0.7974 |
| 0.64 | 3.0 | 2092 | 0.7285 | 0.7731 | 0.7653 | 0.7958 | 0.6867 | 0.7958 |
| 0.5323 | 4.0 | 2790 | 0.7310 | 0.7848 | 0.7758 | 0.8019 | 0.7010 | 0.8019 |
| 0.4717 | 5.0 | 3487 | 0.8139 | 0.7777 | 0.7736 | 0.7924 | 0.6849 | 0.7924 |
| 0.312 | 6.0 | 4185 | 0.8625 | 0.7835 | 0.7761 | 0.7974 | 0.6950 | 0.7974 |
| 0.2707 | 7.0 | 4882 | 0.9528 | 0.7824 | 0.7804 | 0.7910 | 0.6869 | 0.7910 |
| 0.1907 | 8.0 | 5580 | 1.0535 | 0.7814 | 0.7749 | 0.7962 | 0.6902 | 0.7962 |
| 0.1494 | 9.0 | 6277 | 1.1044 | 0.7791 | 0.7761 | 0.7863 | 0.6825 | 0.7863 |
| 0.1408 | 10.0 | 6975 | 1.1593 | 0.7818 | 0.7790 | 0.7879 | 0.6845 | 0.7879 |
| 0.0949 | 11.0 | 7672 | 1.2428 | 0.7846 | 0.7791 | 0.7954 | 0.6920 | 0.7954 |
| 0.0815 | 12.0 | 8370 | 1.2998 | 0.7834 | 0.7770 | 0.7963 | 0.6926 | 0.7963 |
| 0.0657 | 13.0 | 9067 | 1.3431 | 0.7827 | 0.7784 | 0.7929 | 0.6889 | 0.7929 |
| 0.0509 | 14.0 | 9765 | 1.3687 | 0.7813 | 0.7773 | 0.7910 | 0.6863 | 0.7910 |
| 0.0488 | 14.99 | 10455 | 1.3733 | 0.7820 | 0.7773 | 0.7917 | 0.6875 | 0.7917 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.1.0+cu118
- Tokenizers 0.15.0
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