arabic-eou-model-v1
This model is a fine-tuned version of aubmindlab/bert-base-arabertv02-twitter on the xmjo/arabic-eou-dataset-v1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4713
- Accuracy: 0.7922
- Precision: 0.7790
- Recall: 0.8378
- F1: 0.8073
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: 1.5e-05
- train_batch_size: 128
- eval_batch_size: 128
- 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: 3
- label_smoothing_factor: 0.015
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 0.4651 | 40 | 0.5364 | 0.7518 | 0.7183 | 0.8597 | 0.7827 |
| No log | 0.9302 | 80 | 0.4941 | 0.7709 | 0.7511 | 0.8364 | 0.7915 |
| No log | 1.3953 | 120 | 0.4806 | 0.7793 | 0.7479 | 0.8681 | 0.8035 |
| No log | 1.8605 | 160 | 0.4746 | 0.7841 | 0.7573 | 0.8604 | 0.8055 |
| No log | 2.3256 | 200 | 0.4721 | 0.7878 | 0.7681 | 0.8477 | 0.8059 |
| No log | 2.7907 | 240 | 0.4713 | 0.7922 | 0.7790 | 0.8378 | 0.8073 |
Framework versions
- Transformers 4.55.4
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.21.4
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