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NHS-dmis-binary-512
intermezzo672/NHS-dmis-binary-512
NHS-dmis-binary-512 is a text classification model from intermezzo672. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- May 2, 2024
- Updated
- May 2, 2024
- SHA
- 68f73a0d
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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. -->
NHS-dmis-binary-512
This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4235
- Accuracy: 0.8125
- Precision: 0.8080
- Recall: 0.8104
- F1: 0.8090
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: 3e-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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0493 | 1.0 | 397 | 0.4334 | 0.8145 | 0.8078 | 0.8140 | 0.8100 |
| 0.0637 | 2.0 | 794 | 0.5025 | 0.7773 | 0.7959 | 0.8004 | 0.7772 |
| 3.1195 | 3.0 | 1191 | 0.5155 | 0.8240 | 0.8176 | 0.8184 | 0.8180 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- May 2, 2024
- Updated
- May 2, 2024