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---
base_model: aubmindlab/bert-base-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Improved-Arabert-twitter-sentiment2
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-sentiment2
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: 0.4308
- Accuracy: 0.8759
## 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.07 | 50 | 0.4102 | 0.8130 |
| No log | 0.14 | 100 | 0.3141 | 0.8769 |
| No log | 0.21 | 150 | 0.2981 | 0.8806 |
| No log | 0.27 | 200 | 0.3297 | 0.8769 |
| No log | 0.34 | 250 | 0.2998 | 0.8796 |
| No log | 0.41 | 300 | 0.3312 | 0.8630 |
| No log | 0.48 | 350 | 0.3615 | 0.8491 |
| No log | 0.55 | 400 | 0.3695 | 0.8481 |
| No log | 0.62 | 450 | 0.3094 | 0.8778 |
| 0.316 | 0.68 | 500 | 0.2784 | 0.8907 |
| 0.316 | 0.75 | 550 | 0.3404 | 0.8759 |
| 0.316 | 0.82 | 600 | 0.3045 | 0.8806 |
| 0.316 | 0.89 | 650 | 0.3435 | 0.8731 |
| 0.316 | 0.96 | 700 | 0.2849 | 0.9 |
| 0.316 | 1.03 | 750 | 0.2846 | 0.8963 |
| 0.316 | 1.1 | 800 | 0.3034 | 0.8926 |
| 0.316 | 1.16 | 850 | 0.3801 | 0.8787 |
| 0.316 | 1.23 | 900 | 0.3525 | 0.8898 |
| 0.316 | 1.3 | 950 | 0.3388 | 0.8889 |
| 0.2119 | 1.37 | 1000 | 0.3823 | 0.8843 |
| 0.2119 | 1.44 | 1050 | 0.3621 | 0.8935 |
| 0.2119 | 1.51 | 1100 | 0.4106 | 0.8843 |
| 0.2119 | 1.58 | 1150 | 0.3820 | 0.8870 |
| 0.2119 | 1.64 | 1200 | 0.3770 | 0.8796 |
| 0.2119 | 1.71 | 1250 | 0.4199 | 0.8824 |
| 0.2119 | 1.78 | 1300 | 0.4308 | 0.8759 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1
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