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deberta-v3-emotion-multilabel-classifier
ngantuk-banget-wok/deberta-v3-emotion-multilabel-classifier
deberta-v3-emotion-multilabel-classifier is a text classification model from ngantuk-banget-wok. 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
- deberta-v2
- Access
- Public
- Created
- Jun 12, 2025
- Updated
- Jun 12, 2025
- SHA
- 47941791
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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. -->
deberta-v3-emotion-multilabel-classifier
This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1926
- Macro F1: 0.3872
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 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
| Training Loss | Epoch | Step | Validation Loss | Macro F1 |
|---|---|---|---|---|
| 0.2139 | 1.0 | 1307 | 0.2002 | 0.3182 |
| 0.1919 | 2.0 | 2614 | 0.1950 | 0.3742 |
| 0.1816 | 3.0 | 3921 | 0.1926 | 0.3872 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Jun 12, 2025
- Updated
- Jun 12, 2025