---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: AraBERT_token_classification_Araieval24_binary
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# AraBERT_token_classification_Araieval24_binary

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0062
- Precision: 0.1851
- Recall: 0.2340
- F1: 0.2067
- Accuracy: 0.7436

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5408        | 1.0   | 776  | 0.5362          | 0.1292    | 0.1665 | 0.1455 | 0.7566   |
| 0.4664        | 2.0   | 1552 | 0.5402          | 0.1399    | 0.2139 | 0.1692 | 0.7462   |
| 0.3855        | 3.0   | 2328 | 0.5915          | 0.1632    | 0.1935 | 0.1771 | 0.7552   |
| 0.2911        | 4.0   | 3104 | 0.6717          | 0.1712    | 0.1953 | 0.1825 | 0.7457   |
| 0.2334        | 5.0   | 3880 | 0.7420          | 0.1826    | 0.2066 | 0.1939 | 0.7473   |
| 0.18          | 6.0   | 4656 | 0.8034          | 0.1835    | 0.2278 | 0.2033 | 0.7447   |
| 0.1611        | 7.0   | 5432 | 0.8849          | 0.1949    | 0.2275 | 0.2099 | 0.7515   |
| 0.1323        | 8.0   | 6208 | 0.9530          | 0.1870    | 0.2337 | 0.2078 | 0.7449   |
| 0.1133        | 9.0   | 6984 | 1.0043          | 0.1909    | 0.2348 | 0.2106 | 0.7434   |
| 0.1007        | 10.0  | 7760 | 1.0062          | 0.1851    | 0.2340 | 0.2067 | 0.7436   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3