---
library_name: transformers
base_model: aubmindlab/bert-large-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: improved_stance_detection_v2-fold1
  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_stance_detection_v2-fold1

This model is a fine-tuned version of [aubmindlab/bert-large-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-large-arabertv02-twitter) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4010
- Accuracy: 0.5902
- Macro F1: 0.5938
- Weighted F1: 0.5921
- F1 Pro: 0.5891
- F1 Against: 0.5590
- F1 Neutral: 0.6333

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Macro F1 | Weighted F1 | F1 Pro | F1 Against | F1 Neutral |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|:------:|:----------:|:----------:|
| 2.0675        | 1.9320 | 50   | 0.4024          | 0.5854   | 0.5880   | 0.5866      | 0.6056 | 0.5430     | 0.6154     |
| 2.0157        | 3.8544 | 100  | 0.4171          | 0.5073   | 0.4646   | 0.4585      | 0.2558 | 0.4868     | 0.6512     |
| 2.1266        | 5.7767 | 150  | 0.5205          | 0.3073   | 0.1567   | 0.1445      | 0.0    | 0.0        | 0.4701     |
| 2.1044        | 7.6990 | 200  | 0.4990          | 0.3512   | 0.1733   | 0.1826      | 0.0    | 0.5199     | 0.0        |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.9.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2