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# prueba5

This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2442
- Precision: 0.5258
- Recall: 0.5574
- F1: 0.5411
- Accuracy: 0.9609

## 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: 2.75e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 57   | 0.2341          | 0.0       | 0.0    | 0.0    | 0.9488   |
| No log        | 2.0   | 114  | 0.2411          | 0.0       | 0.0    | 0.0    | 0.9488   |
| No log        | 3.0   | 171  | 0.2150          | 0.0385    | 0.0055 | 0.0096 | 0.9410   |
| No log        | 4.0   | 228  | 0.1885          | 0.25      | 0.0929 | 0.1355 | 0.9500   |
| No log        | 5.0   | 285  | 0.1730          | 0.3830    | 0.1967 | 0.2599 | 0.9524   |
| No log        | 6.0   | 342  | 0.1591          | 0.5098    | 0.2842 | 0.3649 | 0.9581   |
| No log        | 7.0   | 399  | 0.1665          | 0.5405    | 0.3279 | 0.4082 | 0.9609   |
| No log        | 8.0   | 456  | 0.1856          | 0.5294    | 0.4918 | 0.5099 | 0.9604   |
| 0.1706        | 9.0   | 513  | 0.1727          | 0.5       | 0.5191 | 0.5094 | 0.9611   |
| 0.1706        | 10.0  | 570  | 0.1717          | 0.5669    | 0.4863 | 0.5235 | 0.9639   |
| 0.1706        | 11.0  | 627  | 0.1913          | 0.5024    | 0.5628 | 0.5309 | 0.9601   |
| 0.1706        | 12.0  | 684  | 0.1793          | 0.515     | 0.5628 | 0.5379 | 0.9619   |
| 0.1706        | 13.0  | 741  | 0.2009          | 0.5679    | 0.5027 | 0.5333 | 0.9618   |
| 0.1706        | 14.0  | 798  | 0.2043          | 0.5333    | 0.5683 | 0.5503 | 0.9604   |
| 0.1706        | 15.0  | 855  | 0.2052          | 0.5486    | 0.5246 | 0.5363 | 0.9629   |
| 0.1706        | 16.0  | 912  | 0.2234          | 0.5183    | 0.5410 | 0.5294 | 0.9581   |
| 0.1706        | 17.0  | 969  | 0.2157          | 0.5424    | 0.5246 | 0.5333 | 0.9616   |
| 0.0202        | 18.0  | 1026 | 0.2207          | 0.5025    | 0.5574 | 0.5285 | 0.9596   |
| 0.0202        | 19.0  | 1083 | 0.2297          | 0.5025    | 0.5410 | 0.5211 | 0.9573   |
| 0.0202        | 20.0  | 1140 | 0.2264          | 0.5131    | 0.5355 | 0.5241 | 0.9593   |
| 0.0202        | 21.0  | 1197 | 0.2300          | 0.5181    | 0.5464 | 0.5319 | 0.9593   |
| 0.0202        | 22.0  | 1254 | 0.2348          | 0.5241    | 0.5355 | 0.5297 | 0.9604   |
| 0.0202        | 23.0  | 1311 | 0.2372          | 0.5196    | 0.5792 | 0.5478 | 0.9588   |
| 0.0202        | 24.0  | 1368 | 0.2349          | 0.5319    | 0.5464 | 0.5391 | 0.9613   |
| 0.0202        | 25.0  | 1425 | 0.2353          | 0.5312    | 0.5574 | 0.544  | 0.9619   |
| 0.0202        | 26.0  | 1482 | 0.2388          | 0.5489    | 0.5519 | 0.5504 | 0.9614   |
| 0.0044        | 27.0  | 1539 | 0.2396          | 0.5243    | 0.5301 | 0.5272 | 0.9618   |
| 0.0044        | 28.0  | 1596 | 0.2442          | 0.5152    | 0.5574 | 0.5354 | 0.9603   |
| 0.0044        | 29.0  | 1653 | 0.2444          | 0.5178    | 0.5574 | 0.5368 | 0.9604   |
| 0.0044        | 30.0  | 1710 | 0.2442          | 0.5258    | 0.5574 | 0.5411 | 0.9609   |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "prueba5", "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 

prueba5
=======


This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2442
* Precision: 0.5258
* Recall: 0.5574
* F1: 0.5411
* Accuracy: 0.9609


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: 2.75e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30


### 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: 2.75e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2
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: 2.75e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2
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: 2.75e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30### Training results### Framework versions


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