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# Bio_ClinicalBERT_fold_2_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: 1.9317
- F1: 0.7921

## 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  | 0.4221          | 0.7856 |
| 0.4062        | 2.0   | 580  | 0.5184          | 0.7949 |
| 0.4062        | 3.0   | 870  | 0.6854          | 0.7840 |
| 0.1775        | 4.0   | 1160 | 0.9834          | 0.7840 |
| 0.1775        | 5.0   | 1450 | 1.3223          | 0.7804 |
| 0.0697        | 6.0   | 1740 | 1.2896          | 0.7923 |
| 0.0265        | 7.0   | 2030 | 1.4620          | 0.7914 |
| 0.0265        | 8.0   | 2320 | 1.5554          | 0.7835 |
| 0.0102        | 9.0   | 2610 | 1.7009          | 0.7880 |
| 0.0102        | 10.0  | 2900 | 1.6163          | 0.7923 |
| 0.015         | 11.0  | 3190 | 1.6851          | 0.7841 |
| 0.015         | 12.0  | 3480 | 1.7493          | 0.7901 |
| 0.0141        | 13.0  | 3770 | 1.8819          | 0.7827 |
| 0.0133        | 14.0  | 4060 | 1.7535          | 0.7939 |
| 0.0133        | 15.0  | 4350 | 1.6613          | 0.7966 |
| 0.0067        | 16.0  | 4640 | 1.6807          | 0.7999 |
| 0.0067        | 17.0  | 4930 | 1.6703          | 0.7978 |
| 0.0053        | 18.0  | 5220 | 1.7309          | 0.8013 |
| 0.0037        | 19.0  | 5510 | 1.8058          | 0.7942 |
| 0.0037        | 20.0  | 5800 | 1.8233          | 0.7916 |
| 0.0023        | 21.0  | 6090 | 1.8206          | 0.7913 |
| 0.0023        | 22.0  | 6380 | 1.8466          | 0.7949 |
| 0.0012        | 23.0  | 6670 | 1.8531          | 0.7985 |
| 0.0012        | 24.0  | 6960 | 1.9211          | 0.7944 |
| 0.0001        | 25.0  | 7250 | 1.9317          | 0.7921 |


### 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_2_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\_2\_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: 1.9317
* F1: 0.7921


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