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BioMedNLP_DeBERTa_all_updates
hongpingjun98/BioMedNLP_DeBERTa_all_updates
BioMedNLP_DeBERTa_all_updates is a text classification model from hongpingjun98. 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
- bert
- Access
- Public
- Created
- Jan 24, 2024
- Updated
- Jan 24, 2024
- SHA
- e01d5a54
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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. -->
BioMedNLP_DeBERTa_all_updates
This model is a fine-tuned version of hongpingjun98/BioMedNLP_DeBERTa on the sem_eval_2024_task_2 dataset. It achieves the following results on the evaluation set:
- Loss: 2.4673
- Accuracy: 0.655
- Precision: 0.6715
- Recall: 0.655
- F1: 0.6465
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
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.3757 | 1.0 | 115 | 0.6988 | 0.7 | 0.7020 | 0.7 | 0.6992 |
| 0.3965 | 2.0 | 230 | 0.7320 | 0.695 | 0.7259 | 0.6950 | 0.6842 |
| 0.3603 | 3.0 | 345 | 0.7736 | 0.7 | 0.7338 | 0.7 | 0.6888 |
| 0.2721 | 4.0 | 460 | 0.8780 | 0.665 | 0.6802 | 0.665 | 0.6578 |
| 0.4003 | 5.0 | 575 | 0.9046 | 0.655 | 0.6796 | 0.655 | 0.6428 |
| 0.2773 | 6.0 | 690 | 0.9664 | 0.7 | 0.7053 | 0.7 | 0.6981 |
| 0.2465 | 7.0 | 805 | 1.0035 | 0.67 | 0.6845 | 0.67 | 0.6634 |
| 0.3437 | 8.0 | 920 | 1.0087 | 0.665 | 0.6780 | 0.665 | 0.6588 |
| 0.1175 | 9.0 | 1035 | 1.2598 | 0.675 | 0.6780 | 0.675 | 0.6736 |
| 0.155 | 10.0 | 1150 | 1.3976 | 0.69 | 0.7038 | 0.69 | 0.6847 |
| 0.1013 | 11.0 | 1265 | 1.3761 | 0.67 | 0.6757 | 0.6700 | 0.6673 |
| 0.1664 | 12.0 | 1380 | 1.5027 | 0.695 | 0.6950 | 0.695 | 0.6950 |
| 0.0847 | 13.0 | 1495 | 1.8199 | 0.685 | 0.6973 | 0.685 | 0.68 |
| 0.0856 | 14.0 | 1610 | 1.8299 | 0.66 | 0.6783 | 0.6600 | 0.6511 |
| 0.1053 | 15.0 | 1725 | 2.0431 | 0.665 | 0.6852 | 0.665 | 0.6556 |
| 0.0958 | 16.0 | 1840 | 1.9203 | 0.7 | 0.7040 | 0.7 | 0.6985 |
| 0.0344 | 17.0 | 1955 | 2.1390 | 0.665 | 0.6780 | 0.665 | 0.6588 |
| 0.014 | 18.0 | 2070 | 2.3609 | 0.655 | 0.6692 | 0.655 | 0.6476 |
| 0.0085 | 19.0 | 2185 | 2.4310 | 0.65 | 0.6671 | 0.65 | 0.6408 |
| 0.0285 | 20.0 | 2300 | 2.4673 | 0.655 | 0.6715 | 0.655 | 0.6465 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Jan 24, 2024
- Updated
- Jan 24, 2024