---
base_model: SI2M-Lab/DarijaBERT-arabizi
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner-DarijaBERT-arabizi
  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. -->

# ner-DarijaBERT-arabizi

This model is a fine-tuned version of [SI2M-Lab/DarijaBERT-arabizi](https://huggingface.co/SI2M-Lab/DarijaBERT-arabizi) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1011
- Precision: 0.7475
- Recall: 0.7753
- F1: 0.7611
- Accuracy: 0.9681

## 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: 64
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 32   | 0.3240          | 0.5397    | 0.3251 | 0.4058 | 0.8996   |
| No log        | 2.0   | 64   | 0.2541          | 0.5593    | 0.4720 | 0.5120 | 0.9203   |
| No log        | 3.0   | 96   | 0.2062          | 0.5697    | 0.5828 | 0.5762 | 0.9350   |
| No log        | 4.0   | 128  | 0.1791          | 0.6162    | 0.6313 | 0.6236 | 0.9426   |
| No log        | 5.0   | 160  | 0.1528          | 0.6504    | 0.6803 | 0.6650 | 0.9509   |
| No log        | 6.0   | 192  | 0.1308          | 0.6880    | 0.7262 | 0.7066 | 0.9582   |
| No log        | 7.0   | 224  | 0.1189          | 0.7126    | 0.7270 | 0.7198 | 0.9612   |
| No log        | 8.0   | 256  | 0.1100          | 0.7307    | 0.7661 | 0.7480 | 0.9651   |
| No log        | 9.0   | 288  | 0.1037          | 0.7423    | 0.7567 | 0.7494 | 0.9667   |
| No log        | 10.0  | 320  | 0.1011          | 0.7475    | 0.7753 | 0.7611 | 0.9681   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0