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bert-base-arabert-finetuned-mdeberta-tn-v2
betteib/bert-base-arabert-finetuned-mdeberta-tn-v2
bert-base-arabert-finetuned-mdeberta-tn-v2 is a fill-mask model from betteib. Use it when you need the model to fill a missing word. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Fill-Mask
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- May 30, 2024
- Updated
- May 30, 2024
- SHA
- dd0fe8fa
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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. -->
bert-base-arabert-finetuned-mdeberta-tn-v2
This model is a fine-tuned version of aubmindlab/bert-base-arabert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.7103
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.7489 | 1.0 | 157 | 4.0242 |
| 3.9609 | 2.0 | 314 | 3.7539 |
| 3.7823 | 3.0 | 471 | 3.7103 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Fill-Mask
- Library
- transformers
- Type
- bert
- Created
- May 30, 2024
- Updated
- May 30, 2024