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Emotion-Detector
Foulbubble/Emotion-Detector
Emotion-Detector is a text classification model from Foulbubble. 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 29, 2024
- Updated
- Jun 29, 2024
- SHA
- 810f8595
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Base models
Datasets
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. -->
Emotion-Detector
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.2559
- Accuracy: 0.9415
- F1: 0.9413
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.3777 | 1.0 | 1000 | 0.1929 | 0.931 | 0.9320 |
| 0.139 | 2.0 | 2000 | 0.1698 | 0.9375 | 0.9365 |
| 0.0998 | 3.0 | 3000 | 0.1635 | 0.942 | 0.9422 |
| 0.0737 | 4.0 | 4000 | 0.2216 | 0.9415 | 0.9416 |
| 0.039 | 5.0 | 5000 | 0.2559 | 0.9415 | 0.9413 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jun 29, 2024
- Updated
- Jun 29, 2024