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# Yepes_5e-05_250

This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1394
- Precision: 0.7129
- Recall: 0.5498
- F1: 0.6208
- Accuracy: 0.9796

## 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: 5e-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
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5163        | 1.39  | 25   | 0.2117          | 0.0       | 0.0    | 0.0    | 0.9672   |
| 0.1988        | 2.78  | 50   | 0.2076          | 0.0       | 0.0    | 0.0    | 0.9672   |
| 0.1579        | 4.17  | 75   | 0.1379          | 0.4017    | 0.2338 | 0.2956 | 0.9712   |
| 0.1055        | 5.56  | 100  | 0.1182          | 0.5688    | 0.3085 | 0.4    | 0.9754   |
| 0.0791        | 6.94  | 125  | 0.1024          | 0.5032    | 0.3955 | 0.4429 | 0.9762   |
| 0.0545        | 8.33  | 150  | 0.1038          | 0.5683    | 0.4453 | 0.4993 | 0.9777   |
| 0.0402        | 9.72  | 175  | 0.1165          | 0.7063    | 0.4726 | 0.5663 | 0.9796   |
| 0.0337        | 11.11 | 200  | 0.1104          | 0.6635    | 0.5149 | 0.5798 | 0.9786   |
| 0.0238        | 12.5  | 225  | 0.1203          | 0.6789    | 0.5522 | 0.6091 | 0.9790   |
| 0.0202        | 13.89 | 250  | 0.1263          | 0.7416    | 0.5498 | 0.6314 | 0.9803   |
| 0.0147        | 15.28 | 275  | 0.1273          | 0.6965    | 0.5423 | 0.6098 | 0.9791   |
| 0.0129        | 16.67 | 300  | 0.1338          | 0.6796    | 0.5647 | 0.6168 | 0.9787   |
| 0.0109        | 18.06 | 325  | 0.1359          | 0.7690    | 0.5547 | 0.6445 | 0.9804   |
| 0.0091        | 19.44 | 350  | 0.1394          | 0.7129    | 0.5498 | 0.6208 | 0.9796   |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "Yepes_5e-05_250", "results": []}]}
transformers pytorch bert token-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

Yepes\_5e-05\_250
=================


This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1394
* Precision: 0.7129
* Recall: 0.5498
* F1: 0.6208
* Accuracy: 0.9796


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: 5e-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
* training\_steps: 500


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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
* training\_steps: 500 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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
* training\_steps: 500 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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
* training\_steps: 500### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2