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# Procedures_Identification_RoBERTa_fine_tuned 

This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-biomedical-clinical-es](https://huggingface.co/PlanTL-GOB-ES/roberta-base-biomedical-clinical-es) on the [MedProcNER dataset] (https://temu.bsc.es/medprocner/). This is a result of the PhD dissertation of Antonio Tamayo.
It achieves the following results on the evaluation set:
- Loss: 0.1820
- Precision: 0.7209
- Recall: 0.7813
- F1: 0.7499
- Accuracy: 0.9659

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1142        | 1.0   | 1132 | 0.1094          | 0.6387    | 0.7417 | 0.6864 | 0.9605   |
| 0.087         | 2.0   | 2264 | 0.1099          | 0.6829    | 0.7557 | 0.7175 | 0.9625   |
| 0.05          | 3.0   | 3396 | 0.1279          | 0.7134    | 0.7651 | 0.7383 | 0.9650   |
| 0.0308        | 4.0   | 4528 | 0.1512          | 0.6720    | 0.7885 | 0.7256 | 0.9611   |
| 0.0201        | 5.0   | 5660 | 0.1643          | 0.7254    | 0.7810 | 0.7521 | 0.9667   |
| 0.0128        | 6.0   | 6792 | 0.1798          | 0.7139    | 0.7832 | 0.7470 | 0.9656   |
| 0.0095        | 7.0   | 7924 | 0.1820          | 0.7209    | 0.7813 | 0.7499 | 0.9659   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "widget": [{"text": "La paciente present\u00f3 anemizaci\u00f3n que ha ido recuperando sin que haya precisado hemotransfusi\u00f3n."}], "model-index": [{"name": "Procedures_Identification_RoBERTa_fine_tuned", "results": []}]}
transformers pytorch tensorboard roberta token-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

Procedures\_Identification\_RoBERTa\_fine\_tuned
================================================


This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-biomedical-clinical-es on the [MedProcNER dataset] (URL This is a result of the PhD dissertation of Antonio Tamayo.
It achieves the following results on the evaluation set:


* Loss: 0.1820
* Precision: 0.7209
* Recall: 0.7813
* F1: 0.7499
* Accuracy: 0.9659


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3