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UIT-UIT-deberta-v3-base-finetuned-finetuned
sercetexam9/UIT-UIT-deberta-v3-base-finetuned-finetuned
UIT-UIT-deberta-v3-base-finetuned-finetuned is a text classification model from sercetexam9. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- deberta-v2
- Access
- Public
- Created
- Jan 22, 2025
- Updated
- Jan 22, 2025
- SHA
- 53ac4771
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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. -->
UIT-UIT-deberta-v3-base-finetuned-finetuned
This model is a fine-tuned version of sercetexam9/UIT-deberta-v3-base-finetuned on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2498
- F1: 0.7479
- Roc Auc: 0.8121
- Accuracy: 0.4856
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.0039 | 1.0 | 139 | 1.1766 | 0.7316 | 0.7956 | 0.4585 |
| 0.009 | 2.0 | 278 | 1.2260 | 0.7294 | 0.7986 | 0.4801 |
| 0.0176 | 3.0 | 417 | 1.2442 | 0.7198 | 0.7970 | 0.4711 |
| 0.0079 | 4.0 | 556 | 1.2818 | 0.7256 | 0.7864 | 0.4675 |
| 0.0042 | 5.0 | 695 | 1.3645 | 0.6821 | 0.7580 | 0.4458 |
| 0.0023 | 6.0 | 834 | 1.2464 | 0.7348 | 0.8012 | 0.4747 |
| 0.0012 | 7.0 | 973 | 1.2399 | 0.7217 | 0.7933 | 0.4675 |
| 0.0048 | 8.0 | 1112 | 1.2350 | 0.7401 | 0.8087 | 0.4765 |
| 0.0065 | 9.0 | 1251 | 1.2247 | 0.7467 | 0.8120 | 0.4910 |
| 0.0008 | 10.0 | 1390 | 1.2747 | 0.7377 | 0.7989 | 0.4892 |
| 0.0029 | 11.0 | 1529 | 1.2528 | 0.7248 | 0.7954 | 0.4657 |
| 0.0005 | 12.0 | 1668 | 1.3288 | 0.7312 | 0.7911 | 0.4801 |
| 0.0002 | 13.0 | 1807 | 1.2498 | 0.7479 | 0.8121 | 0.4856 |
| 0.0009 | 14.0 | 1946 | 1.2460 | 0.7335 | 0.7990 | 0.4856 |
| 0.0001 | 15.0 | 2085 | 1.2580 | 0.7348 | 0.7989 | 0.4892 |
| 0.0001 | 16.0 | 2224 | 1.2552 | 0.7373 | 0.8007 | 0.4910 |
| 0.0002 | 17.0 | 2363 | 1.2601 | 0.7389 | 0.8014 | 0.4964 |
| 0.0001 | 18.0 | 2502 | 1.2585 | 0.7390 | 0.8019 | 0.4982 |
| 0.0001 | 19.0 | 2641 | 1.2593 | 0.7395 | 0.8023 | 0.4982 |
| 0.0001 | 20.0 | 2780 | 1.2591 | 0.7401 | 0.8026 | 0.4982 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Jan 22, 2025
- Updated
- Jan 22, 2025