---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: M11
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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---
This model was trained on data without unique labels.
---
# M11

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0194
- Accuracy: 0.9974
- Precision: 0.9961
- Recall: 0.9987
- F1: 0.9974

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.0269        | 1.0   | 21116  | 0.0205          | 0.9961   | 0.9941    | 0.9981 | 0.9961 |
| 0.012         | 2.0   | 42232  | 0.0179          | 0.9968   | 0.9963    | 0.9974 | 0.9968 |
| 0.0067        | 3.0   | 63348  | 0.0201          | 0.9972   | 0.9971    | 0.9972 | 0.9972 |
| 0.0042        | 4.0   | 84464  | 0.0180          | 0.9975   | 0.9962    | 0.9987 | 0.9975 |
| 0.0028        | 5.0   | 105580 | 0.0194          | 0.9974   | 0.9961    | 0.9987 | 0.9974 |


### Framework versions

- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1