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Bio_ClinicalBERT_fold_3_binary_v1
elopezlopez/Bio_ClinicalBERT_fold_3_binary_v1
Bio_ClinicalBERT_fold_3_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
- df0f72c2
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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_3_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: 1.8860
- F1: 0.8051
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 | 289 | 0.4493 | 0.7916 |
| 0.3975 | 2.0 | 578 | 0.4608 | 0.7909 |
| 0.3975 | 3.0 | 867 | 0.8364 | 0.7726 |
| 0.1885 | 4.0 | 1156 | 1.0380 | 0.7902 |
| 0.1885 | 5.0 | 1445 | 1.1612 | 0.7921 |
| 0.0692 | 6.0 | 1734 | 1.3894 | 0.7761 |
| 0.0295 | 7.0 | 2023 | 1.3730 | 0.7864 |
| 0.0295 | 8.0 | 2312 | 1.4131 | 0.7939 |
| 0.0161 | 9.0 | 2601 | 1.5538 | 0.7929 |
| 0.0161 | 10.0 | 2890 | 1.6417 | 0.7931 |
| 0.006 | 11.0 | 3179 | 1.5745 | 0.7974 |
| 0.006 | 12.0 | 3468 | 1.7212 | 0.7908 |
| 0.0132 | 13.0 | 3757 | 1.7349 | 0.7945 |
| 0.0062 | 14.0 | 4046 | 1.7593 | 0.7908 |
| 0.0062 | 15.0 | 4335 | 1.7420 | 0.8035 |
| 0.0073 | 16.0 | 4624 | 1.7620 | 0.8007 |
| 0.0073 | 17.0 | 4913 | 1.8286 | 0.7908 |
| 0.0033 | 18.0 | 5202 | 1.7863 | 0.7977 |
| 0.0033 | 19.0 | 5491 | 1.9275 | 0.7919 |
| 0.0035 | 20.0 | 5780 | 1.8481 | 0.8042 |
| 0.0035 | 21.0 | 6069 | 1.9465 | 0.8012 |
| 0.0035 | 22.0 | 6358 | 1.8177 | 0.8044 |
| 0.005 | 23.0 | 6647 | 1.8615 | 0.8030 |
| 0.005 | 24.0 | 6936 | 1.8427 | 0.8054 |
| 0.0011 | 25.0 | 7225 | 1.8860 | 0.8051 |
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