---
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