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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: 0.7828
- Macro F1: 0.9002
- Precision: 0.8999
- Recall: 0.9007
- Kappa: 0.8082
- Accuracy: 0.9007
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:--------:|
| 0.492 | 1.0 | 697 | 0.3226 | 0.8904 | 0.8920 | 0.8923 | 0.7872 | 0.8923 |
| 0.3283 | 2.0 | 1395 | 0.3107 | 0.9000 | 0.9001 | 0.9010 | 0.8071 | 0.9010 |
| 0.2371 | 3.0 | 2092 | 0.3224 | 0.8959 | 0.8973 | 0.8949 | 0.8020 | 0.8949 |
| 0.1817 | 4.0 | 2790 | 0.3469 | 0.9000 | 0.9007 | 0.9000 | 0.8082 | 0.9000 |
| 0.1372 | 5.0 | 3487 | 0.4185 | 0.8966 | 0.8980 | 0.8962 | 0.8034 | 0.8962 |
| 0.0779 | 6.0 | 4185 | 0.4717 | 0.8989 | 0.8991 | 0.8992 | 0.8059 | 0.8992 |
| 0.0676 | 7.0 | 4882 | 0.5415 | 0.8962 | 0.8972 | 0.8958 | 0.8014 | 0.8958 |
| 0.042 | 8.0 | 5580 | 0.6031 | 0.8984 | 0.8988 | 0.8982 | 0.8057 | 0.8982 |
| 0.0335 | 9.0 | 6277 | 0.6551 | 0.9017 | 0.9019 | 0.9025 | 0.8106 | 0.9025 |
| 0.0239 | 10.0 | 6975 | 0.7116 | 0.8975 | 0.8974 | 0.8980 | 0.8029 | 0.8980 |
| 0.0168 | 11.0 | 7672 | 0.7130 | 0.8976 | 0.8976 | 0.8984 | 0.8029 | 0.8984 |
| 0.019 | 12.0 | 8370 | 0.7464 | 0.9011 | 0.9007 | 0.9018 | 0.8101 | 0.9018 |
| 0.0121 | 13.0 | 9067 | 0.7709 | 0.9006 | 0.9003 | 0.9010 | 0.8091 | 0.9010 |
| 0.0089 | 14.0 | 9765 | 0.7790 | 0.9002 | 0.9002 | 0.9007 | 0.8081 | 0.9007 |
| 0.0068 | 14.99 | 10455 | 0.7828 | 0.9002 | 0.8999 | 0.9007 | 0.8082 | 0.9007 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.1.0+cu118
- Tokenizers 0.15.0
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