
<!-- 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_9_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: 1.6976
- F1: 0.8065

## 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   | 291  | 0.4002          | 0.7826 |
| 0.4094        | 2.0   | 582  | 0.3968          | 0.8212 |
| 0.4094        | 3.0   | 873  | 0.6130          | 0.7984 |
| 0.1977        | 4.0   | 1164 | 0.5853          | 0.8227 |
| 0.1977        | 5.0   | 1455 | 0.9401          | 0.8143 |
| 0.0837        | 6.0   | 1746 | 1.1764          | 0.8059 |
| 0.0274        | 7.0   | 2037 | 1.1515          | 0.8112 |
| 0.0274        | 8.0   | 2328 | 1.2614          | 0.8065 |
| 0.0113        | 9.0   | 2619 | 1.3404          | 0.8002 |
| 0.0113        | 10.0  | 2910 | 1.3926          | 0.8088 |
| 0.0125        | 11.0  | 3201 | 1.4539          | 0.8010 |
| 0.0125        | 12.0  | 3492 | 1.5460          | 0.7998 |
| 0.0101        | 13.0  | 3783 | 1.5920          | 0.8060 |
| 0.0107        | 14.0  | 4074 | 1.5631          | 0.8059 |
| 0.0107        | 15.0  | 4365 | 1.6323          | 0.8020 |
| 0.0127        | 16.0  | 4656 | 1.6183          | 0.8008 |
| 0.0127        | 17.0  | 4947 | 1.6351          | 0.8033 |
| 0.0068        | 18.0  | 5238 | 1.5608          | 0.8121 |
| 0.0047        | 19.0  | 5529 | 1.6339          | 0.8141 |
| 0.0047        | 20.0  | 5820 | 1.6039          | 0.8091 |
| 0.0029        | 21.0  | 6111 | 1.5676          | 0.8085 |
| 0.0029        | 22.0  | 6402 | 1.6489          | 0.8139 |
| 0.0036        | 23.0  | 6693 | 1.6824          | 0.8087 |
| 0.0036        | 24.0  | 6984 | 1.6773          | 0.8106 |
| 0.0008        | 25.0  | 7275 | 1.6976          | 0.8065 |


### 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_9_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\_9\_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: 1.6976
* F1: 0.8065


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