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# Yepes_2e-05_31_03

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: 0.0955
- Precision: 0.6940
- Recall: 0.5159
- F1: 0.5918
- Accuracy: 0.9824

## 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
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.7814        | 1.92  | 25   | 0.2044          | 0.0       | 0.0    | 0.0    | 0.9704   |
| 0.1936        | 3.85  | 50   | 0.1853          | 0.0       | 0.0    | 0.0    | 0.9704   |
| 0.1651        | 5.77  | 75   | 0.1260          | 0.1667    | 0.0714 | 0.1    | 0.9714   |
| 0.1129        | 7.69  | 100  | 0.1127          | 0.3532    | 0.2354 | 0.2825 | 0.9761   |
| 0.0906        | 9.62  | 125  | 0.1029          | 0.4878    | 0.3175 | 0.3846 | 0.9788   |
| 0.0773        | 11.54 | 150  | 0.0990          | 0.5059    | 0.3386 | 0.4057 | 0.9797   |
| 0.0621        | 13.46 | 175  | 0.0908          | 0.5486    | 0.4180 | 0.4745 | 0.9793   |
| 0.0568        | 15.38 | 200  | 0.0875          | 0.6212    | 0.4339 | 0.5109 | 0.9811   |
| 0.0462        | 17.31 | 225  | 0.0900          | 0.6413    | 0.4683 | 0.5413 | 0.9817   |
| 0.0403        | 19.23 | 250  | 0.0936          | 0.6797    | 0.4603 | 0.5489 | 0.9823   |
| 0.0372        | 21.15 | 275  | 0.0895          | 0.6516    | 0.4947 | 0.5624 | 0.9819   |
| 0.0333        | 23.08 | 300  | 0.0925          | 0.6643    | 0.4974 | 0.5688 | 0.9823   |
| 0.0285        | 25.0  | 325  | 0.0962          | 0.6871    | 0.5053 | 0.5823 | 0.9822   |
| 0.0262        | 26.92 | 350  | 0.0955          | 0.6940    | 0.5159 | 0.5918 | 0.9824   |


### 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_2e-05_31_03", "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\_2e-05\_31\_03
====================


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: 0.0955
* Precision: 0.6940
* Recall: 0.5159
* F1: 0.5918
* Accuracy: 0.9824


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
* 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: 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
* 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: 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
* 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: 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
* training\_steps: 500### Training results### Framework versions


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