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distilbert-base-uncased-finetuned-emotion
ultimecia/distilbert-base-uncased-finetuned-emotion
distilbert-base-uncased-finetuned-emotion is a text classification model from ultimecia. 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
- Feb 27, 2024
- Updated
- Feb 27, 2024
- SHA
- 6077ac7b
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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. -->
distilbert-base-uncased-finetuned-emotion
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: 0.1910
- Accuracy: 0.9385
- F1: 0.9385
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: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 63 | 0.3110 | 0.907 | 0.9066 |
| No log | 2.0 | 126 | 0.2093 | 0.9255 | 0.9264 |
| No log | 3.0 | 189 | 0.1683 | 0.931 | 0.9312 |
| 0.2667 | 4.0 | 252 | 0.1564 | 0.932 | 0.9319 |
| 0.2667 | 5.0 | 315 | 0.1541 | 0.9325 | 0.9328 |
| 0.2667 | 6.0 | 378 | 0.1577 | 0.9375 | 0.9378 |
| 0.2667 | 7.0 | 441 | 0.1547 | 0.9355 | 0.9357 |
| 0.0894 | 8.0 | 504 | 0.1528 | 0.9385 | 0.9386 |
| 0.0894 | 9.0 | 567 | 0.1630 | 0.9395 | 0.9394 |
| 0.0894 | 10.0 | 630 | 0.1745 | 0.9425 | 0.9427 |
| 0.0894 | 11.0 | 693 | 0.1635 | 0.9385 | 0.9385 |
| 0.0567 | 12.0 | 756 | 0.1706 | 0.938 | 0.9381 |
| 0.0567 | 13.0 | 819 | 0.1740 | 0.941 | 0.9413 |
| 0.0567 | 14.0 | 882 | 0.1766 | 0.94 | 0.9403 |
| 0.0567 | 15.0 | 945 | 0.1832 | 0.938 | 0.9382 |
| 0.0397 | 16.0 | 1008 | 0.1871 | 0.9385 | 0.9388 |
| 0.0397 | 17.0 | 1071 | 0.1889 | 0.938 | 0.9382 |
| 0.0397 | 18.0 | 1134 | 0.1908 | 0.935 | 0.9354 |
| 0.0397 | 19.0 | 1197 | 0.1907 | 0.94 | 0.9399 |
| 0.0284 | 20.0 | 1260 | 0.1910 | 0.9385 | 0.9385 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Feb 27, 2024
- Updated
- Feb 27, 2024