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Bio_ClinicalBERT_fold_6_binary_v1
elopezlopez/Bio_ClinicalBERT_fold_6_binary_v1
Bio_ClinicalBERT_fold_6_binary_v1 is a text classification model from elopezlopez. 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
- Aug 3, 2022
- Updated
- Aug 4, 2022
- SHA
- 8b4916e1
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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. -->
Bio_ClinicalBERT_fold_6_binary_v1
This model is a fine-tuned version of emilyalsentzer/Bio_ClinicalBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7858
- F1: 0.8079
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 290 | 0.4223 | 0.7938 |
| 0.4052 | 2.0 | 580 | 0.4262 | 0.7991 |
| 0.4052 | 3.0 | 870 | 0.5859 | 0.8201 |
| 0.1894 | 4.0 | 1160 | 0.9158 | 0.7859 |
| 0.1894 | 5.0 | 1450 | 1.0524 | 0.8018 |
| 0.0845 | 6.0 | 1740 | 1.0179 | 0.8041 |
| 0.038 | 7.0 | 2030 | 1.2477 | 0.8047 |
| 0.038 | 8.0 | 2320 | 1.2635 | 0.8111 |
| 0.014 | 9.0 | 2610 | 1.4297 | 0.8018 |
| 0.014 | 10.0 | 2900 | 1.4499 | 0.8034 |
| 0.0119 | 11.0 | 3190 | 1.4388 | 0.8194 |
| 0.0119 | 12.0 | 3480 | 1.4813 | 0.8082 |
| 0.0145 | 13.0 | 3770 | 1.5423 | 0.8063 |
| 0.006 | 14.0 | 4060 | 1.5658 | 0.8104 |
| 0.006 | 15.0 | 4350 | 1.6268 | 0.8052 |
| 0.0021 | 16.0 | 4640 | 1.6671 | 0.8148 |
| 0.0021 | 17.0 | 4930 | 1.7222 | 0.8132 |
| 0.005 | 18.0 | 5220 | 1.7973 | 0.8014 |
| 0.0031 | 19.0 | 5510 | 1.7613 | 0.8054 |
| 0.0031 | 20.0 | 5800 | 1.7653 | 0.8071 |
| 0.0099 | 21.0 | 6090 | 1.7343 | 0.7996 |
| 0.0099 | 22.0 | 6380 | 1.7679 | 0.8104 |
| 0.0015 | 23.0 | 6670 | 1.7916 | 0.8095 |
| 0.0015 | 24.0 | 6960 | 1.7815 | 0.8062 |
| 0.0028 | 25.0 | 7250 | 1.7858 | 0.8079 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Aug 3, 2022
- Updated
- Aug 4, 2022