---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: M12-BERT-SIMILIARITY
  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. -->

# M12-BERT-SIMILIARITY

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: 0.2225
- Accuracy: 0.9344
- Precision: 0.8927
- Recall: 0.9873
- F1: 0.9377

## 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     |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2303        | 1.0   | 49975  | 0.2080          | 0.9372   | 0.9036    | 0.9787 | 0.9397 |
| 0.2109        | 2.0   | 99950  | 0.2342          | 0.9337   | 0.8952    | 0.9825 | 0.9368 |
| 0.203         | 3.0   | 149925 | 0.2192          | 0.9375   | 0.9070    | 0.9749 | 0.9397 |
| 0.1962        | 4.0   | 199900 | 0.2225          | 0.9344   | 0.8927    | 0.9873 | 0.9377 |


### Framework versions

- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1