---
base_model: aubmindlab/bert-base-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Improved-Arabert-twitter-sentiment-No-dropout-Twitter
  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. -->

# Improved-Arabert-twitter-sentiment-No-dropout-Twitter

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-base-arabertv02-twitter) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6342
- Accuracy: 0.89

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5264        | 0.55  | 50   | 0.5252          | 0.71     |
| 0.3041        | 1.1   | 100  | 0.4085          | 0.81     |
| 0.2205        | 1.65  | 150  | 0.3303          | 0.88     |
| 0.1476        | 2.2   | 200  | 0.3890          | 0.87     |
| 0.1219        | 2.75  | 250  | 0.3775          | 0.87     |
| 0.0972        | 3.3   | 300  | 0.3930          | 0.88     |
| 0.0917        | 3.85  | 350  | 0.4728          | 0.86     |
| 0.0596        | 4.4   | 400  | 0.4406          | 0.89     |
| 0.0556        | 4.95  | 450  | 0.4949          | 0.89     |
| 0.0375        | 5.49  | 500  | 0.4935          | 0.9      |
| 0.0269        | 6.04  | 550  | 0.5977          | 0.88     |
| 0.0235        | 6.59  | 600  | 0.5543          | 0.89     |
| 0.0191        | 7.14  | 650  | 0.5941          | 0.88     |
| 0.0109        | 7.69  | 700  | 0.6562          | 0.89     |
| 0.0198        | 8.24  | 750  | 0.6342          | 0.89     |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1