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NADI-Country-DID-MARBERTv2
ashabrawy/NADI-Country-DID-MARBERTv2
NADI-Country-DID-MARBERTv2 is a text classification model from ashabrawy. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Aug 24, 2025
- Updated
- Aug 24, 2025
- SHA
- f55c286f
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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. -->
NADI-Country-DID-MARBERTv2
This model is a fine-tuned version of UBC-NLP/MARBERTv2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.9474
- Accuracy: 0.3212
- F1: 0.3031
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 2.5971 | 1.0 | 883 | 2.4084 | 0.2990 | 0.2699 |
| 1.5502 | 2.0 | 1766 | 2.4697 | 0.3207 | 0.3072 |
| 0.9672 | 3.0 | 2649 | 2.6677 | 0.3222 | 0.3057 |
| 0.6248 | 4.0 | 3532 | 2.8501 | 0.3152 | 0.2951 |
| 0.5022 | 5.0 | 4415 | 2.9474 | 0.3212 | 0.3031 |
Framework versions
- Transformers 4.55.2
- Pytorch 2.8.0+cu128
- Datasets 2.16.0
- Tokenizers 0.21.4
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Aug 24, 2025
- Updated
- Aug 24, 2025