Commit ·
887967e
1
Parent(s): 8cb34d2
update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,83 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- f1
|
| 7 |
+
model-index:
|
| 8 |
+
- name: Bio_ClinicalBERT_fold_4_binary_v1
|
| 9 |
+
results: []
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 13 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 14 |
+
|
| 15 |
+
# Bio_ClinicalBERT_fold_4_binary_v1
|
| 16 |
+
|
| 17 |
+
This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset.
|
| 18 |
+
It achieves the following results on the evaluation set:
|
| 19 |
+
- Loss: 1.4627
|
| 20 |
+
- F1: 0.8342
|
| 21 |
+
|
| 22 |
+
## Model description
|
| 23 |
+
|
| 24 |
+
More information needed
|
| 25 |
+
|
| 26 |
+
## Intended uses & limitations
|
| 27 |
+
|
| 28 |
+
More information needed
|
| 29 |
+
|
| 30 |
+
## Training and evaluation data
|
| 31 |
+
|
| 32 |
+
More information needed
|
| 33 |
+
|
| 34 |
+
## Training procedure
|
| 35 |
+
|
| 36 |
+
### Training hyperparameters
|
| 37 |
+
|
| 38 |
+
The following hyperparameters were used during training:
|
| 39 |
+
- learning_rate: 2e-05
|
| 40 |
+
- train_batch_size: 16
|
| 41 |
+
- eval_batch_size: 16
|
| 42 |
+
- seed: 42
|
| 43 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 44 |
+
- lr_scheduler_type: linear
|
| 45 |
+
- num_epochs: 25
|
| 46 |
+
|
| 47 |
+
### Training results
|
| 48 |
+
|
| 49 |
+
| Training Loss | Epoch | Step | Validation Loss | F1 |
|
| 50 |
+
|:-------------:|:-----:|:----:|:---------------:|:------:|
|
| 51 |
+
| No log | 1.0 | 289 | 0.3641 | 0.8394 |
|
| 52 |
+
| 0.3953 | 2.0 | 578 | 0.3729 | 0.8294 |
|
| 53 |
+
| 0.3953 | 3.0 | 867 | 0.6156 | 0.8126 |
|
| 54 |
+
| 0.189 | 4.0 | 1156 | 0.7389 | 0.8326 |
|
| 55 |
+
| 0.189 | 5.0 | 1445 | 0.8925 | 0.8322 |
|
| 56 |
+
| 0.0783 | 6.0 | 1734 | 1.0909 | 0.8196 |
|
| 57 |
+
| 0.0219 | 7.0 | 2023 | 1.1241 | 0.8346 |
|
| 58 |
+
| 0.0219 | 8.0 | 2312 | 1.2684 | 0.8130 |
|
| 59 |
+
| 0.0136 | 9.0 | 2601 | 1.2615 | 0.8202 |
|
| 60 |
+
| 0.0136 | 10.0 | 2890 | 1.2477 | 0.8401 |
|
| 61 |
+
| 0.0143 | 11.0 | 3179 | 1.3211 | 0.8254 |
|
| 62 |
+
| 0.0143 | 12.0 | 3468 | 1.2627 | 0.8286 |
|
| 63 |
+
| 0.0165 | 13.0 | 3757 | 1.3804 | 0.8264 |
|
| 64 |
+
| 0.006 | 14.0 | 4046 | 1.3213 | 0.8414 |
|
| 65 |
+
| 0.006 | 15.0 | 4335 | 1.3152 | 0.8427 |
|
| 66 |
+
| 0.0117 | 16.0 | 4624 | 1.3373 | 0.8368 |
|
| 67 |
+
| 0.0117 | 17.0 | 4913 | 1.3599 | 0.8406 |
|
| 68 |
+
| 0.0021 | 18.0 | 5202 | 1.4072 | 0.8237 |
|
| 69 |
+
| 0.0021 | 19.0 | 5491 | 1.3893 | 0.8336 |
|
| 70 |
+
| 0.0045 | 20.0 | 5780 | 1.4331 | 0.8391 |
|
| 71 |
+
| 0.0049 | 21.0 | 6069 | 1.4128 | 0.8370 |
|
| 72 |
+
| 0.0049 | 22.0 | 6358 | 1.4660 | 0.8356 |
|
| 73 |
+
| 0.0029 | 23.0 | 6647 | 1.4721 | 0.8388 |
|
| 74 |
+
| 0.0029 | 24.0 | 6936 | 1.4636 | 0.8329 |
|
| 75 |
+
| 0.0023 | 25.0 | 7225 | 1.4627 | 0.8342 |
|
| 76 |
+
|
| 77 |
+
|
| 78 |
+
### Framework versions
|
| 79 |
+
|
| 80 |
+
- Transformers 4.21.0
|
| 81 |
+
- Pytorch 1.12.0+cu113
|
| 82 |
+
- Datasets 2.4.0
|
| 83 |
+
- Tokenizers 0.12.1
|