---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fine_tuned_mix50k_arabert_similarity
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# fine_tuned_mix50k_arabert_similarity

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: 0.5527
- Accuracy: 0.8802
- Precision: 0.9022
- Recall: 0.8227
- F1: 0.8606

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3452        | 1.0   | 9862  | 0.3132          | 0.8737   | 0.8774    | 0.8358 | 0.8561 |
| 0.2496        | 2.0   | 19724 | 0.2931          | 0.8778   | 0.8678    | 0.8589 | 0.8633 |
| 0.1939        | 3.0   | 29586 | 0.3597          | 0.8774   | 0.9047    | 0.8128 | 0.8563 |
| 0.1553        | 4.0   | 39448 | 0.4949          | 0.8788   | 0.8843    | 0.8402 | 0.8617 |
| 0.1219        | 5.0   | 49310 | 0.5527          | 0.8802   | 0.9022    | 0.8227 | 0.8606 |


### Framework versions

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