---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mdeberta-v3-base-subjectivity-sentiment-arabic
  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. -->

# mdeberta-v3-base-subjectivity-sentiment-arabic

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7442
- Macro F1: 0.5426
- Macro P: 0.5472
- Macro R: 0.5442
- Subj F1: 0.4457
- Subj P: 0.4910
- Subj R: 0.4080
- Accuracy: 0.5632

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro P | Macro R | Subj F1 | Subj P | Subj R | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------:|:-------:|:-------:|:------:|:------:|:--------:|
| No log        | 1.0   | 153  | 0.6885          | 0.5224   | 0.5299  | 0.5268  | 0.4068  | 0.4706 | 0.3582 | 0.5503   |
| No log        | 2.0   | 306  | 0.6932          | 0.5204   | 0.5602  | 0.5416  | 0.3510  | 0.5248 | 0.2637 | 0.5803   |
| No log        | 3.0   | 459  | 0.6928          | 0.5480   | 0.5748  | 0.5589  | 0.4087  | 0.5410 | 0.3284 | 0.5910   |
| 0.6721        | 4.0   | 612  | 0.7125          | 0.5485   | 0.5492  | 0.5500  | 0.5059  | 0.4820 | 0.5323 | 0.5525   |
| 0.6721        | 5.0   | 765  | 0.7238          | 0.5220   | 0.5667  | 0.5448  | 0.3490  | 0.5361 | 0.2587 | 0.5846   |
| 0.6721        | 6.0   | 918  | 0.7442          | 0.5426   | 0.5472  | 0.5442  | 0.4457  | 0.4910 | 0.4080 | 0.5632   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0