---
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