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distilbert-base-uncased-finetuned-emotion-Exam
888Brogaard/distilbert-base-uncased-finetuned-emotion-Exam
distilbert-base-uncased-finetuned-emotion-Exam is a text classification model from 888Brogaard. 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
- Sep 5, 2024
- Updated
- Sep 10, 2024
- SHA
- 8f7212a1
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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-Exam
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: 0.2916
- Accuracy: 0.939
- F1: 0.9389
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: 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 |
|---|---|---|---|---|---|
| 0.7534 | 1.0 | 250 | 0.2356 | 0.9225 | 0.9231 |
| 0.1908 | 2.0 | 500 | 0.1660 | 0.9375 | 0.9367 |
| 0.1282 | 3.0 | 750 | 0.1470 | 0.9335 | 0.9343 |
| 0.1007 | 4.0 | 1000 | 0.1548 | 0.939 | 0.9394 |
| 0.0852 | 5.0 | 1250 | 0.1540 | 0.9395 | 0.9397 |
| 0.0702 | 6.0 | 1500 | 0.1618 | 0.941 | 0.9410 |
| 0.0591 | 7.0 | 1750 | 0.1847 | 0.9385 | 0.9378 |
| 0.0456 | 8.0 | 2000 | 0.1971 | 0.9355 | 0.9357 |
| 0.037 | 9.0 | 2250 | 0.2337 | 0.9365 | 0.9367 |
| 0.03 | 10.0 | 2500 | 0.2270 | 0.939 | 0.9395 |
| 0.0251 | 11.0 | 2750 | 0.2449 | 0.934 | 0.9340 |
| 0.021 | 12.0 | 3000 | 0.2454 | 0.939 | 0.9390 |
| 0.0182 | 13.0 | 3250 | 0.2613 | 0.9345 | 0.9346 |
| 0.0187 | 14.0 | 3500 | 0.2558 | 0.9375 | 0.9377 |
| 0.0127 | 15.0 | 3750 | 0.2765 | 0.9365 | 0.9364 |
| 0.0112 | 16.0 | 4000 | 0.2873 | 0.9375 | 0.9375 |
| 0.0107 | 17.0 | 4250 | 0.2828 | 0.938 | 0.9382 |
| 0.0091 | 18.0 | 4500 | 0.2866 | 0.937 | 0.9371 |
| 0.0081 | 19.0 | 4750 | 0.2894 | 0.9385 | 0.9384 |
| 0.0072 | 20.0 | 5000 | 0.2916 | 0.939 | 0.9389 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Sep 5, 2024
- Updated
- Sep 10, 2024