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# prueba

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: 0.1440
- Precision: 0.6923
- Recall: 0.6096
- F1: 0.6483
- Accuracy: 0.9719

## 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: 2.5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 32

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 29   | 0.3513          | 0.0       | 0.0    | 0.0    | 0.9259   |
| No log        | 2.0   | 58   | 0.2696          | 0.0       | 0.0    | 0.0    | 0.9259   |
| No log        | 3.0   | 87   | 0.2879          | 0.0       | 0.0    | 0.0    | 0.9259   |
| No log        | 4.0   | 116  | 0.2318          | 0.0714    | 0.0080 | 0.0143 | 0.9361   |
| No log        | 5.0   | 145  | 0.2055          | 0.2222    | 0.0558 | 0.0892 | 0.9376   |
| No log        | 6.0   | 174  | 0.2076          | 0.3793    | 0.0876 | 0.1424 | 0.9464   |
| No log        | 7.0   | 203  | 0.1630          | 0.4831    | 0.2271 | 0.3089 | 0.9525   |
| No log        | 8.0   | 232  | 0.1529          | 0.5515    | 0.3625 | 0.4375 | 0.9573   |
| No log        | 9.0   | 261  | 0.1519          | 0.5972    | 0.3426 | 0.4354 | 0.9603   |
| No log        | 10.0  | 290  | 0.1399          | 0.6272    | 0.4223 | 0.5048 | 0.9639   |
| No log        | 11.0  | 319  | 0.1412          | 0.6096    | 0.4542 | 0.5205 | 0.9641   |
| No log        | 12.0  | 348  | 0.1320          | 0.5969    | 0.4661 | 0.5235 | 0.9646   |
| No log        | 13.0  | 377  | 0.1311          | 0.6515    | 0.5139 | 0.5746 | 0.9671   |
| No log        | 14.0  | 406  | 0.1300          | 0.6329    | 0.5219 | 0.5721 | 0.9656   |
| No log        | 15.0  | 435  | 0.1346          | 0.6345    | 0.4980 | 0.5580 | 0.9672   |
| No log        | 16.0  | 464  | 0.1361          | 0.6329    | 0.5219 | 0.5721 | 0.9669   |
| No log        | 17.0  | 493  | 0.1312          | 0.6532    | 0.5777 | 0.6131 | 0.9689   |
| 0.1181        | 18.0  | 522  | 0.1327          | 0.6756    | 0.6056 | 0.6387 | 0.9694   |
| 0.1181        | 19.0  | 551  | 0.1495          | 0.7234    | 0.5418 | 0.6196 | 0.9704   |
| 0.1181        | 20.0  | 580  | 0.1328          | 0.6872    | 0.5777 | 0.6277 | 0.9707   |
| 0.1181        | 21.0  | 609  | 0.1363          | 0.6667    | 0.6215 | 0.6433 | 0.9710   |
| 0.1181        | 22.0  | 638  | 0.1392          | 0.6884    | 0.5896 | 0.6352 | 0.9712   |
| 0.1181        | 23.0  | 667  | 0.1377          | 0.6437    | 0.6335 | 0.6386 | 0.9704   |
| 0.1181        | 24.0  | 696  | 0.1434          | 0.6504    | 0.5857 | 0.6164 | 0.9697   |
| 0.1181        | 25.0  | 725  | 0.1418          | 0.6944    | 0.5976 | 0.6424 | 0.9710   |
| 0.1181        | 26.0  | 754  | 0.1426          | 0.6739    | 0.6175 | 0.6445 | 0.9715   |
| 0.1181        | 27.0  | 783  | 0.1447          | 0.7085    | 0.6295 | 0.6667 | 0.9734   |
| 0.1181        | 28.0  | 812  | 0.1432          | 0.6903    | 0.6215 | 0.6541 | 0.9727   |
| 0.1181        | 29.0  | 841  | 0.1421          | 0.7162    | 0.6335 | 0.6723 | 0.9729   |
| 0.1181        | 30.0  | 870  | 0.1431          | 0.6875    | 0.6135 | 0.6484 | 0.9720   |
| 0.1181        | 31.0  | 899  | 0.1431          | 0.6844    | 0.6135 | 0.6471 | 0.9717   |
| 0.1181        | 32.0  | 928  | 0.1440          | 0.6923    | 0.6096 | 0.6483 | 0.9719   |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

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

prueba
======


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: 0.1440
* Precision: 0.6923
* Recall: 0.6096
* F1: 0.6483
* Accuracy: 0.9719


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: 2.5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 32


### Training results



### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2.5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 32 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* 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: 2.5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 32 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* 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: 2.5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 32### Training results### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2