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# prueba3

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: 0.2158
- Precision: 0.7162
- Recall: 0.6335
- F1: 0.6723
- Accuracy: 0.9737

## 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: 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 29   | 0.2562          | 0.7732    | 0.5976 | 0.6742 | 0.9719   |
| No log        | 2.0   | 58   | 0.2526          | 0.705     | 0.5618 | 0.6253 | 0.9704   |
| No log        | 3.0   | 87   | 0.2187          | 0.6833    | 0.6534 | 0.6680 | 0.9705   |
| No log        | 4.0   | 116  | 0.2205          | 0.6583    | 0.6295 | 0.6436 | 0.9715   |
| No log        | 5.0   | 145  | 0.2161          | 0.7162    | 0.6534 | 0.6833 | 0.9712   |
| No log        | 6.0   | 174  | 0.2293          | 0.6977    | 0.5976 | 0.6438 | 0.9722   |
| No log        | 7.0   | 203  | 0.2207          | 0.6972    | 0.6056 | 0.6482 | 0.9724   |
| No log        | 8.0   | 232  | 0.2343          | 0.6781    | 0.6295 | 0.6529 | 0.9707   |
| No log        | 9.0   | 261  | 0.2212          | 0.7115    | 0.5896 | 0.6449 | 0.9730   |
| No log        | 10.0  | 290  | 0.2171          | 0.7260    | 0.6016 | 0.6580 | 0.9734   |
| No log        | 11.0  | 319  | 0.2191          | 0.6851    | 0.6414 | 0.6626 | 0.9725   |
| No log        | 12.0  | 348  | 0.2101          | 0.7056    | 0.6494 | 0.6763 | 0.9740   |
| No log        | 13.0  | 377  | 0.2227          | 0.7240    | 0.6375 | 0.6780 | 0.9732   |
| No log        | 14.0  | 406  | 0.2226          | 0.7442    | 0.6375 | 0.6867 | 0.9739   |
| No log        | 15.0  | 435  | 0.2247          | 0.7339    | 0.6375 | 0.6823 | 0.9739   |
| No log        | 16.0  | 464  | 0.2167          | 0.6983    | 0.6454 | 0.6708 | 0.9729   |
| No log        | 17.0  | 493  | 0.2220          | 0.7281    | 0.6295 | 0.6752 | 0.9732   |
| 0.0005        | 18.0  | 522  | 0.2294          | 0.7299    | 0.6135 | 0.6667 | 0.9725   |
| 0.0005        | 19.0  | 551  | 0.2104          | 0.6949    | 0.6534 | 0.6735 | 0.9722   |
| 0.0005        | 20.0  | 580  | 0.2103          | 0.7240    | 0.6375 | 0.6780 | 0.9730   |
| 0.0005        | 21.0  | 609  | 0.2092          | 0.7137    | 0.6454 | 0.6778 | 0.9735   |
| 0.0005        | 22.0  | 638  | 0.2091          | 0.7181    | 0.6494 | 0.6820 | 0.9737   |
| 0.0005        | 23.0  | 667  | 0.2081          | 0.7162    | 0.6534 | 0.6833 | 0.9735   |
| 0.0005        | 24.0  | 696  | 0.2198          | 0.7264    | 0.6135 | 0.6652 | 0.9722   |
| 0.0005        | 25.0  | 725  | 0.2206          | 0.7290    | 0.6215 | 0.6710 | 0.9725   |
| 0.0005        | 26.0  | 754  | 0.2194          | 0.7256    | 0.6215 | 0.6695 | 0.9735   |
| 0.0005        | 27.0  | 783  | 0.2220          | 0.7290    | 0.6215 | 0.6710 | 0.9739   |
| 0.0005        | 28.0  | 812  | 0.2230          | 0.7290    | 0.6215 | 0.6710 | 0.9735   |
| 0.0005        | 29.0  | 841  | 0.2163          | 0.7182    | 0.6295 | 0.6709 | 0.9737   |
| 0.0005        | 30.0  | 870  | 0.2158          | 0.7162    | 0.6335 | 0.6723 | 0.9737   |


### 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": "prueba3", "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 

prueba3
=======


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: 0.2158
* Precision: 0.7162
* Recall: 0.6335
* F1: 0.6723
* Accuracy: 0.9737


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: 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: 30


### 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: 2.75e-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: 30 ### 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: 2.75e-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: 30 ### 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: 2.75e-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: 30### Training results### Framework versions


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