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library_name: transformers
base_model: aubmindlab/bert-base-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Twitter_concatenatewithPrompttrainval-fold4
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. -->
# Twitter_concatenatewithPrompttrainval-fold4
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: 0.3952
- Accuracy: 0.875
- Macro F1: 0.8733
- Weighted F1: 0.8746
- F1 Pro: 0.9123
- F1 Against: 0.8760
- F1 Neutral: 0.8317
## 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: 16
- eval_batch_size: 16
- seed: 42
- 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: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Weighted F1 | F1 Pro | F1 Against | F1 Neutral |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|:------:|:----------:|:----------:|
| 0.9326 | 1.1628 | 50 | 0.5759 | 0.7798 | 0.7792 | 0.7787 | 0.8305 | 0.7304 | 0.7767 |
| 0.5335 | 2.3256 | 100 | 0.4192 | 0.8333 | 0.8332 | 0.8335 | 0.8571 | 0.8226 | 0.82 |
| 0.3503 | 3.4884 | 150 | 0.4169 | 0.8452 | 0.8439 | 0.8449 | 0.8929 | 0.8346 | 0.8041 |
| 0.2399 | 4.6512 | 200 | 0.3952 | 0.875 | 0.8733 | 0.8746 | 0.9123 | 0.8760 | 0.8317 |
### Framework versions
- Transformers 5.0.0
- Pytorch 2.9.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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