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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: 1.3454
- Macro F1: 0.7875
- Precision: 0.7834
- Recall: 0.7949
- Kappa: 0.6913
- Accuracy: 0.7949
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:--------:|
| 1.1521 | 1.0 | 697 | 0.7730 | 0.7668 | 0.7492 | 0.7976 | 0.6831 | 0.7976 |
| 0.7985 | 2.0 | 1395 | 0.7075 | 0.7817 | 0.7674 | 0.8003 | 0.6965 | 0.8003 |
| 0.6333 | 3.0 | 2092 | 0.7101 | 0.7840 | 0.7793 | 0.8078 | 0.7023 | 0.8078 |
| 0.5307 | 4.0 | 2790 | 0.7471 | 0.7797 | 0.7779 | 0.7989 | 0.6929 | 0.7989 |
| 0.447 | 5.0 | 3487 | 0.7967 | 0.7826 | 0.7765 | 0.7951 | 0.6916 | 0.7951 |
| 0.304 | 6.0 | 4185 | 0.8912 | 0.7884 | 0.7836 | 0.7976 | 0.6961 | 0.7976 |
| 0.2597 | 7.0 | 4882 | 0.9286 | 0.7872 | 0.7820 | 0.7962 | 0.6925 | 0.7962 |
| 0.1859 | 8.0 | 5580 | 1.0321 | 0.7887 | 0.7845 | 0.7996 | 0.6963 | 0.7996 |
| 0.1542 | 9.0 | 6277 | 1.0918 | 0.7840 | 0.7801 | 0.7926 | 0.6879 | 0.7926 |
| 0.135 | 10.0 | 6975 | 1.1611 | 0.7884 | 0.7825 | 0.8035 | 0.6988 | 0.8035 |
| 0.0894 | 11.0 | 7672 | 1.2353 | 0.7866 | 0.7862 | 0.7911 | 0.6871 | 0.7911 |
| 0.084 | 12.0 | 8370 | 1.2618 | 0.7875 | 0.7832 | 0.7965 | 0.6920 | 0.7965 |
| 0.0595 | 13.0 | 9067 | 1.3147 | 0.7847 | 0.7836 | 0.7879 | 0.6844 | 0.7879 |
| 0.0472 | 14.0 | 9765 | 1.3424 | 0.7872 | 0.7839 | 0.7942 | 0.6897 | 0.7942 |
| 0.0422 | 14.99 | 10455 | 1.3454 | 0.7875 | 0.7834 | 0.7949 | 0.6913 | 0.7949 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.1.0+cu118
- Tokenizers 0.15.0
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