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---
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: 1.0885
- Macro F1: 0.7537
- Precision: 0.7463
- Recall: 0.7783
- Kappa: 0.6636
- Accuracy: 0.7783
## 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 | 101 | 1.2153 | 0.5786 | 0.5030 | 0.6835 | 0.4719 | 0.6835 |
| No log | 2.0 | 203 | 1.0583 | 0.6615 | 0.6707 | 0.7365 | 0.5699 | 0.7365 |
| No log | 3.0 | 304 | 0.9495 | 0.6925 | 0.6934 | 0.7525 | 0.6069 | 0.7525 |
| No log | 4.0 | 406 | 0.8934 | 0.7325 | 0.7283 | 0.7635 | 0.6400 | 0.7635 |
| 0.976 | 5.0 | 507 | 0.9247 | 0.7219 | 0.7166 | 0.7660 | 0.6352 | 0.7660 |
| 0.976 | 6.0 | 609 | 0.8751 | 0.7502 | 0.7422 | 0.7685 | 0.6594 | 0.7685 |
| 0.976 | 7.0 | 710 | 0.9145 | 0.7510 | 0.7395 | 0.7783 | 0.6640 | 0.7783 |
| 0.976 | 8.0 | 812 | 0.9934 | 0.7479 | 0.7423 | 0.7808 | 0.6609 | 0.7808 |
| 0.976 | 9.0 | 913 | 0.9641 | 0.7506 | 0.7425 | 0.7734 | 0.6594 | 0.7734 |
| 0.3286 | 10.0 | 1015 | 0.9702 | 0.7560 | 0.7587 | 0.7746 | 0.6641 | 0.7746 |
| 0.3286 | 11.0 | 1116 | 1.0610 | 0.7430 | 0.7370 | 0.7746 | 0.6530 | 0.7746 |
| 0.3286 | 12.0 | 1218 | 1.0251 | 0.7537 | 0.7442 | 0.7722 | 0.6611 | 0.7722 |
| 0.3286 | 13.0 | 1319 | 1.0703 | 0.7511 | 0.7433 | 0.7771 | 0.6615 | 0.7771 |
| 0.3286 | 14.0 | 1421 | 1.0767 | 0.7534 | 0.7451 | 0.7771 | 0.6631 | 0.7771 |
| 0.1456 | 14.93 | 1515 | 1.0885 | 0.7537 | 0.7463 | 0.7783 | 0.6636 | 0.7783 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3
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