pytorch tensorboard bert text-classification transformers generated_from_trainer model-index
---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fine-tuned-arabert-random-negative
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# fine-tuned-arabert-random-negative

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0080
- Accuracy: 0.9989
- Precision: 0.9990
- Recall: 0.9988
- F1: 0.9989

## 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     |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.0105        | 1.0   | 62920  | 0.0061          | 0.9986   | 0.9993    | 0.9979 | 0.9986 |
| 0.0069        | 2.0   | 125840 | 0.0096          | 0.9986   | 0.9993    | 0.9979 | 0.9986 |
| 0.0058        | 3.0   | 188760 | 0.0084          | 0.9988   | 0.9988    | 0.9988 | 0.9988 |
| 0.0047        | 4.0   | 251680 | 0.0080          | 0.9989   | 0.9990    | 0.9988 | 0.9989 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
