---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: anercorpDataset_v2.1
  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. -->

# anercorpDataset_v2.1

This model is a fine-tuned version of [CAMeL-Lab/bert-base-arabic-camelbert-mix-ner](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2755
- Precision: 0.7604
- Recall: 0.6878
- F1: 0.7223
- Accuracy: 0.9461

## 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: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.206         | 1.0   | 7057  | 0.2703          | 0.6971    | 0.6367 | 0.6655 | 0.9377   |
| 0.2036        | 2.0   | 14114 | 0.2438          | 0.7460    | 0.6756 | 0.7090 | 0.9449   |
| 0.1404        | 3.0   | 21171 | 0.2755          | 0.7604    | 0.6878 | 0.7223 | 0.9461   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3