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---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: Bio_ClinicalBERT_fold_7_binary_v1
results: []
---
<!-- 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_7_binary_v1
This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6855
- F1: 0.8169
## 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 | 288 | 0.4412 | 0.7939 |
| 0.4021 | 2.0 | 576 | 0.4104 | 0.8116 |
| 0.4021 | 3.0 | 864 | 0.6152 | 0.8059 |
| 0.1893 | 4.0 | 1152 | 0.8887 | 0.8135 |
| 0.1893 | 5.0 | 1440 | 1.0395 | 0.7930 |
| 0.08 | 6.0 | 1728 | 1.1491 | 0.7992 |
| 0.0296 | 7.0 | 2016 | 1.2957 | 0.8028 |
| 0.0296 | 8.0 | 2304 | 1.3748 | 0.8067 |
| 0.0168 | 9.0 | 2592 | 1.3284 | 0.8077 |
| 0.0168 | 10.0 | 2880 | 1.3705 | 0.8100 |
| 0.0151 | 11.0 | 3168 | 1.4993 | 0.8015 |
| 0.0151 | 12.0 | 3456 | 1.4156 | 0.8152 |
| 0.0072 | 13.0 | 3744 | 1.4199 | 0.8108 |
| 0.0105 | 14.0 | 4032 | 1.4797 | 0.8086 |
| 0.0105 | 15.0 | 4320 | 1.4374 | 0.8244 |
| 0.0101 | 16.0 | 4608 | 1.5125 | 0.8142 |
| 0.0101 | 17.0 | 4896 | 1.5709 | 0.8131 |
| 0.0105 | 18.0 | 5184 | 1.6013 | 0.8146 |
| 0.0105 | 19.0 | 5472 | 1.5923 | 0.8150 |
| 0.0039 | 20.0 | 5760 | 1.6233 | 0.8179 |
| 0.0009 | 21.0 | 6048 | 1.5644 | 0.8203 |
| 0.0009 | 22.0 | 6336 | 1.6229 | 0.8218 |
| 0.001 | 23.0 | 6624 | 1.6706 | 0.8157 |
| 0.001 | 24.0 | 6912 | 1.6754 | 0.8166 |
| 0.0013 | 25.0 | 7200 | 1.6855 | 0.8169 |
### Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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