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distilbert-base-uncased-finetuned-emotion
steve202608/distilbert-base-uncased-finetuned-emotion
distilbert-base-uncased-finetuned-emotion is a text classification model from steve202608. 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
- Aug 1, 2026
- Updated
- Aug 1, 2026
- SHA
- 73efff7c
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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-base-uncased-finetuned-emotion
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1922
- Accuracy: 0.9365
- F1: 0.9364
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: 128
- eval_batch_size: 128
- 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
- num_epochs: 16
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.0338 | 1.0 | 125 | 0.4268 | 0.8755 | 0.8667 |
| 0.2848 | 2.0 | 250 | 0.2057 | 0.928 | 0.9285 |
| 0.1571 | 3.0 | 375 | 0.1687 | 0.9355 | 0.9360 |
| 0.1195 | 4.0 | 500 | 0.1462 | 0.935 | 0.9356 |
| 0.0995 | 5.0 | 625 | 0.1474 | 0.9345 | 0.9346 |
| 0.0829 | 6.0 | 750 | 0.1498 | 0.936 | 0.9362 |
| 0.0758 | 7.0 | 875 | 0.1517 | 0.9335 | 0.9333 |
| 0.0649 | 8.0 | 1000 | 0.1571 | 0.935 | 0.9351 |
| 0.0536 | 9.0 | 1125 | 0.1622 | 0.9385 | 0.9383 |
| 0.0453 | 10.0 | 1250 | 0.1678 | 0.937 | 0.9370 |
| 0.0400 | 11.0 | 1375 | 0.1752 | 0.938 | 0.9380 |
| 0.0354 | 12.0 | 1500 | 0.1839 | 0.938 | 0.9379 |
| 0.0295 | 13.0 | 1625 | 0.1868 | 0.938 | 0.9378 |
| 0.0279 | 14.0 | 1750 | 0.1912 | 0.9365 | 0.9369 |
| 0.0271 | 15.0 | 1875 | 0.1942 | 0.9385 | 0.9383 |
| 0.0212 | 16.0 | 2000 | 0.1922 | 0.9365 | 0.9364 |
Framework versions
- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Aug 1, 2026
- Updated
- Aug 1, 2026