---
base_model: Ammar-alhaj-ali/arabic-MARBERT-sentiment
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: unfortified_marbert2
  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. -->

# unfortified_marbert2

This model is a fine-tuned version of [Ammar-alhaj-ali/arabic-MARBERT-sentiment](https://huggingface.co/Ammar-alhaj-ali/arabic-MARBERT-sentiment) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1953
- Accuracy: 0.91

## 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        | 0.0546 | 50   | 0.3250          | 0.87     |
| No log        | 0.1092 | 100  | 0.2651          | 0.91     |
| No log        | 0.1638 | 150  | 0.4169          | 0.84     |
| No log        | 0.2183 | 200  | 0.3473          | 0.89     |
| No log        | 0.2729 | 250  | 0.3455          | 0.88     |
| No log        | 0.3275 | 300  | 0.2863          | 0.9      |
| No log        | 0.3821 | 350  | 0.2220          | 0.93     |
| No log        | 0.4367 | 400  | 0.2382          | 0.92     |
| No log        | 0.4913 | 450  | 0.3704          | 0.89     |
| 0.2918        | 0.5459 | 500  | 0.2641          | 0.92     |
| 0.2918        | 0.6004 | 550  | 0.2706          | 0.9      |
| 0.2918        | 0.6550 | 600  | 0.1759          | 0.93     |
| 0.2918        | 0.7096 | 650  | 0.3032          | 0.92     |
| 0.2918        | 0.7642 | 700  | 0.1880          | 0.91     |
| 0.2918        | 0.8188 | 750  | 0.2076          | 0.92     |
| 0.2918        | 0.8734 | 800  | 0.3046          | 0.91     |
| 0.2918        | 0.9279 | 850  | 0.1953          | 0.91     |


### Framework versions

- Transformers 4.42.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1