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my_arabic_POS_model
Mennatullah-Tarek/my_arabic_POS_model
my_arabic_POS_model is a token classification model from Mennatullah-Tarek. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- May 8, 2025
- Updated
- May 8, 2025
- SHA
- a8fb6f7a
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Base models
Model card
From the Hugging Face model README
<!-- 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. -->
my_arabic_POS_model
This model is a fine-tuned version of asafaya/bert-base-arabic on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1028
- Precision: 0.9629
- Recall: 0.9589
- F1: 0.9609
- Accuracy: 0.9726
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 3
Training results
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- Created
- May 8, 2025
- Updated
- May 8, 2025