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# Bio_ClinicalBERT_fold_9_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: 2.0189
- F1: 0.7905

## 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   | 292  | 0.5758          | 0.7571 |
| 0.5482        | 2.0   | 584  | 0.6282          | 0.7609 |
| 0.5482        | 3.0   | 876  | 0.6823          | 0.7841 |
| 0.2346        | 4.0   | 1168 | 0.9898          | 0.7776 |
| 0.2346        | 5.0   | 1460 | 1.1397          | 0.7866 |
| 0.1001        | 6.0   | 1752 | 1.3832          | 0.7751 |
| 0.0447        | 7.0   | 2044 | 1.6002          | 0.7674 |
| 0.0447        | 8.0   | 2336 | 1.7265          | 0.7584 |
| 0.0171        | 9.0   | 2628 | 1.6650          | 0.7699 |
| 0.0171        | 10.0  | 2920 | 1.7322          | 0.7661 |
| 0.0156        | 11.0  | 3212 | 1.8071          | 0.7789 |
| 0.012         | 12.0  | 3504 | 1.8322          | 0.7841 |
| 0.012         | 13.0  | 3796 | 1.8948          | 0.7763 |
| 0.01          | 14.0  | 4088 | 1.7667          | 0.7918 |
| 0.01          | 15.0  | 4380 | 1.8538          | 0.7879 |
| 0.0063        | 16.0  | 4672 | 1.9763          | 0.7776 |
| 0.0063        | 17.0  | 4964 | 1.9970          | 0.7841 |
| 0.0028        | 18.0  | 5256 | 1.9366          | 0.7931 |
| 0.0003        | 19.0  | 5548 | 1.9709          | 0.7892 |
| 0.0003        | 20.0  | 5840 | 1.9460          | 0.7879 |
| 0.0044        | 21.0  | 6132 | 2.0280          | 0.7866 |
| 0.0044        | 22.0  | 6424 | 1.9423          | 0.7918 |
| 0.0013        | 23.0  | 6716 | 1.9618          | 0.7918 |
| 0.004         | 24.0  | 7008 | 2.0241          | 0.7905 |
| 0.004         | 25.0  | 7300 | 2.0189          | 0.7905 |


### 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_9_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\_9\_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: 2.0189
* F1: 0.7905


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