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# Bio_ClinicalBERT_fold_10_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: 1.5504
- F1: 0.8243

## 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  | 0.3803          | 0.8103 |
| 0.4005        | 2.0   | 576  | 0.4769          | 0.8070 |
| 0.4005        | 3.0   | 864  | 0.5258          | 0.7955 |
| 0.1889        | 4.0   | 1152 | 0.7423          | 0.8153 |
| 0.1889        | 5.0   | 1440 | 1.1246          | 0.8012 |
| 0.0703        | 6.0   | 1728 | 1.1325          | 0.8039 |
| 0.0246        | 7.0   | 2016 | 1.2192          | 0.8196 |
| 0.0246        | 8.0   | 2304 | 1.3645          | 0.8050 |
| 0.0192        | 9.0   | 2592 | 1.4029          | 0.8087 |
| 0.0192        | 10.0  | 2880 | 1.3714          | 0.8117 |
| 0.0107        | 11.0  | 3168 | 1.4673          | 0.8092 |
| 0.0107        | 12.0  | 3456 | 1.3941          | 0.8199 |
| 0.0084        | 13.0  | 3744 | 1.4350          | 0.8126 |
| 0.0083        | 14.0  | 4032 | 1.4428          | 0.8162 |
| 0.0083        | 15.0  | 4320 | 1.2892          | 0.8263 |
| 0.0119        | 16.0  | 4608 | 1.4238          | 0.8222 |
| 0.0119        | 17.0  | 4896 | 1.4961          | 0.8174 |
| 0.0046        | 18.0  | 5184 | 1.5010          | 0.8107 |
| 0.0046        | 19.0  | 5472 | 1.4876          | 0.8215 |
| 0.0036        | 20.0  | 5760 | 1.5080          | 0.8180 |
| 0.0031        | 21.0  | 6048 | 1.5317          | 0.8261 |
| 0.0031        | 22.0  | 6336 | 1.5103          | 0.8215 |
| 0.0005        | 23.0  | 6624 | 1.5255          | 0.8197 |
| 0.0005        | 24.0  | 6912 | 1.5578          | 0.8257 |
| 0.0001        | 25.0  | 7200 | 1.5504          | 0.8243 |


### Framework versions

- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "Bio_ClinicalBERT_fold_10_binary_v1", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

Bio\_ClinicalBERT\_fold\_10\_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: 1.5504
* F1: 0.8243


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



### Framework versions


* Transformers 4.21.0
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### 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 ### Framework versions


* Transformers 4.21.0
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.21.0
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### 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### Framework versions


* Transformers 4.21.0
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1