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bertweet
Isabeljuradoj27/bertweet
bertweet is a text classification model from Isabeljuradoj27. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- May 19, 2026
- Updated
- May 19, 2026
- SHA
- 4dd8fb62
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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. -->
bertweet
This model is a fine-tuned version of vinai/bertweet-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5801
- F1 Macro: 0.7714
- Accuracy: 0.8182
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: 32
- eval_batch_size: 32
- 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
- lr_scheduler_warmup_steps: 50
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | Accuracy |
|---|---|---|---|---|---|
| 0.8738 | 1.0 | 102 | 0.7906 | 0.6790 | 0.7460 |
| 0.5740 | 2.0 | 204 | 0.6487 | 0.7257 | 0.7861 |
| 0.4364 | 3.0 | 306 | 0.5768 | 0.7507 | 0.8021 |
| 0.3546 | 4.0 | 408 | 0.5904 | 0.7660 | 0.8155 |
| 0.2665 | 5.0 | 510 | 0.5801 | 0.7714 | 0.8182 |
Framework versions
- Transformers 5.3.0
- Pytorch 2.8.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- May 19, 2026
- Updated
- May 19, 2026