
<!-- 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_2_ternary_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: 1.8186
- F1: 0.8038

## 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   | 294  | 0.5629          | 0.7645 |
| 0.5579        | 2.0   | 588  | 0.5078          | 0.8078 |
| 0.5579        | 3.0   | 882  | 0.6622          | 0.7754 |
| 0.2341        | 4.0   | 1176 | 0.8584          | 0.7943 |
| 0.2341        | 5.0   | 1470 | 1.1953          | 0.7821 |
| 0.0942        | 6.0   | 1764 | 1.3193          | 0.7876 |
| 0.0338        | 7.0   | 2058 | 1.3324          | 0.7903 |
| 0.0338        | 8.0   | 2352 | 1.5043          | 0.7930 |
| 0.0202        | 9.0   | 2646 | 1.5255          | 0.7889 |
| 0.0202        | 10.0  | 2940 | 1.5382          | 0.7916 |
| 0.0119        | 11.0  | 3234 | 1.6377          | 0.7903 |
| 0.0051        | 12.0  | 3528 | 1.7349          | 0.7835 |
| 0.0051        | 13.0  | 3822 | 1.7297          | 0.7835 |
| 0.0082        | 14.0  | 4116 | 1.7817          | 0.7808 |
| 0.0082        | 15.0  | 4410 | 1.7105          | 0.7970 |
| 0.0054        | 16.0  | 4704 | 1.7325          | 0.7984 |
| 0.0054        | 17.0  | 4998 | 1.7919          | 0.7943 |
| 0.0049        | 18.0  | 5292 | 1.8850          | 0.7876 |
| 0.0045        | 19.0  | 5586 | 1.8237          | 0.7916 |
| 0.0045        | 20.0  | 5880 | 1.8760          | 0.7970 |
| 0.0024        | 21.0  | 6174 | 1.8544          | 0.7984 |
| 0.0024        | 22.0  | 6468 | 1.7852          | 0.8011 |
| 0.0005        | 23.0  | 6762 | 1.7795          | 0.8065 |
| 0.0031        | 24.0  | 7056 | 1.7978          | 0.7997 |
| 0.0031        | 25.0  | 7350 | 1.8186          | 0.8038 |


### Framework versions

- Transformers 4.21.1
- 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_ternary_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\_ternary\_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: 1.8186
* F1: 0.8038


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 4.21.1
* 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 4.21.1
* 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 4.21.1
* 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 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1