---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: AraBERT_token_classification_Araieval24_binary_all_data
  results: []
---

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# AraBERT_token_classification_Araieval24_binary_all_data

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: 0.6550
- Precision: 0.1699
- Recall: 0.2317
- F1: 0.1960
- Accuracy: 0.7589

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4925        | 1.0   | 1495  | 0.5219          | 0.1768    | 0.1444 | 0.1589 | 0.7688   |
| 0.4596        | 2.0   | 2990  | 0.5213          | 0.1275    | 0.1950 | 0.1542 | 0.7560   |
| 0.4273        | 3.0   | 4485  | 0.5231          | 0.1459    | 0.2094 | 0.1720 | 0.7658   |
| 0.4008        | 4.0   | 5980  | 0.5287          | 0.1722    | 0.1925 | 0.1818 | 0.7709   |
| 0.3783        | 5.0   | 7475  | 0.5650          | 0.1667    | 0.2242 | 0.1913 | 0.7646   |
| 0.3592        | 6.0   | 8970  | 0.6256          | 0.1763    | 0.2289 | 0.1992 | 0.7647   |
| 0.3427        | 7.0   | 10465 | 0.6223          | 0.1756    | 0.2256 | 0.1975 | 0.7651   |
| 0.3273        | 8.0   | 11960 | 0.5932          | 0.1691    | 0.2244 | 0.1929 | 0.7608   |
| 0.3199        | 9.0   | 13455 | 0.6602          | 0.1789    | 0.2207 | 0.1976 | 0.7647   |
| 0.3067        | 10.0  | 14950 | 0.6550          | 0.1699    | 0.2317 | 0.1960 | 0.7589   |


### Framework versions

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