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distilbert-emotion-multilabel-classifier-v2
wintertia/distilbert-emotion-multilabel-classifier-v2
distilbert-emotion-multilabel-classifier-v2 is a text classification model from wintertia. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Jun 11, 2025
- Updated
- Jun 11, 2025
- SHA
- bdb92bd5
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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. -->
distilbert-emotion-multilabel-classifier-v2
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1938
- F1 Macro: 0.3790
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: 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro |
|---|---|---|---|---|
| 0.2702 | 1.0 | 581 | 0.2058 | 0.2230 |
| 0.2012 | 2.0 | 1162 | 0.1954 | 0.3137 |
| 0.1882 | 3.0 | 1743 | 0.1933 | 0.3556 |
| 0.1811 | 4.0 | 2324 | 0.1935 | 0.3710 |
| 0.1749 | 5.0 | 2905 | 0.1938 | 0.3790 |
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
- distilbert
- License
- apache-2.0
- Created
- Jun 11, 2025
- Updated
- Jun 11, 2025