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# Disease_Identification_RoBERTa_fine_tuned_Testing

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 [DisTEMIST dataset] (https://temu.bsc.es/distemist/). This is a result of the PhD dissertation of Antonio Tamayo.
It achieves the following results on the evaluation set:
- Loss: 0.1665
- Precision: 0.7235
- Recall: 0.7528
- F1: 0.7378
- Accuracy: 0.9727

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0897        | 1.0   | 1504  | 0.0885          | 0.6534    | 0.6868 | 0.6697 | 0.9693   |
| 0.0626        | 2.0   | 3008  | 0.0899          | 0.6654    | 0.7532 | 0.7066 | 0.9687   |
| 0.0421        | 3.0   | 4512  | 0.1010          | 0.7121    | 0.7204 | 0.7162 | 0.9717   |
| 0.0268        | 4.0   | 6016  | 0.1180          | 0.7318    | 0.7427 | 0.7372 | 0.9725   |
| 0.0166        | 5.0   | 7520  | 0.1438          | 0.7225    | 0.7450 | 0.7336 | 0.9722   |
| 0.0086        | 6.0   | 9024  | 0.1603          | 0.7179    | 0.7532 | 0.7351 | 0.9724   |
| 0.0056        | 7.0   | 10528 | 0.1665          | 0.7235    | 0.7528 | 0.7378 | 0.9727   |


### 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": "Disease_Identification_RoBERTa_fine_tuned_Testing", "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 

Disease\_Identification\_RoBERTa\_fine\_tuned\_Testing
======================================================


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


* Loss: 0.1665
* Precision: 0.7235
* Recall: 0.7528
* F1: 0.7378
* Accuracy: 0.9727


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