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# prueba1

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: 0.1842
- Precision: 0.7072
- Recall: 0.6255
- F1: 0.6638
- Accuracy: 0.9724

## 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: 3.5e-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   | 0.1520          | 0.5625    | 0.6813 | 0.6162 | 0.9659   |
| No log        | 2.0   | 58   | 0.1552          | 0.6293    | 0.5817 | 0.6046 | 0.9686   |
| No log        | 3.0   | 87   | 0.1586          | 0.6667    | 0.5737 | 0.6167 | 0.9709   |
| No log        | 4.0   | 116  | 0.1595          | 0.6981    | 0.5896 | 0.6393 | 0.9722   |
| No log        | 5.0   | 145  | 0.1699          | 0.6729    | 0.5737 | 0.6194 | 0.9676   |
| No log        | 6.0   | 174  | 0.1753          | 0.6577    | 0.5817 | 0.6173 | 0.9689   |
| No log        | 7.0   | 203  | 0.1665          | 0.6540    | 0.6175 | 0.6352 | 0.9681   |
| No log        | 8.0   | 232  | 0.1792          | 0.7157    | 0.5618 | 0.6295 | 0.9712   |
| No log        | 9.0   | 261  | 0.1682          | 0.7048    | 0.5896 | 0.6421 | 0.9714   |
| No log        | 10.0  | 290  | 0.1732          | 0.7366    | 0.6016 | 0.6623 | 0.9724   |
| No log        | 11.0  | 319  | 0.1663          | 0.672     | 0.6693 | 0.6707 | 0.9725   |
| No log        | 12.0  | 348  | 0.1882          | 0.7071    | 0.5578 | 0.6236 | 0.9692   |
| No log        | 13.0  | 377  | 0.1825          | 0.7103    | 0.6056 | 0.6538 | 0.9710   |
| No log        | 14.0  | 406  | 0.1755          | 0.7164    | 0.5737 | 0.6372 | 0.9709   |
| No log        | 15.0  | 435  | 0.1950          | 0.6842    | 0.5697 | 0.6217 | 0.9689   |
| No log        | 16.0  | 464  | 0.1660          | 0.7240    | 0.6375 | 0.6780 | 0.9727   |
| No log        | 17.0  | 493  | 0.1833          | 0.7255    | 0.5896 | 0.6505 | 0.9724   |
| 0.0061        | 18.0  | 522  | 0.1832          | 0.7190    | 0.6016 | 0.6551 | 0.9702   |
| 0.0061        | 19.0  | 551  | 0.1762          | 0.6828    | 0.6175 | 0.6485 | 0.9707   |
| 0.0061        | 20.0  | 580  | 0.1785          | 0.7346    | 0.6175 | 0.6710 | 0.9734   |
| 0.0061        | 21.0  | 609  | 0.1791          | 0.7093    | 0.6414 | 0.6736 | 0.9739   |
| 0.0061        | 22.0  | 638  | 0.1843          | 0.7476    | 0.6255 | 0.6811 | 0.9737   |
| 0.0061        | 23.0  | 667  | 0.1837          | 0.7371    | 0.6255 | 0.6767 | 0.9734   |
| 0.0061        | 24.0  | 696  | 0.1867          | 0.7176    | 0.6175 | 0.6638 | 0.9715   |
| 0.0061        | 25.0  | 725  | 0.1844          | 0.7089    | 0.6016 | 0.6509 | 0.9710   |
| 0.0061        | 26.0  | 754  | 0.1815          | 0.7072    | 0.6255 | 0.6638 | 0.9725   |
| 0.0061        | 27.0  | 783  | 0.1822          | 0.7021    | 0.6574 | 0.6790 | 0.9737   |
| 0.0061        | 28.0  | 812  | 0.1853          | 0.7048    | 0.6375 | 0.6695 | 0.9732   |
| 0.0061        | 29.0  | 841  | 0.1845          | 0.7069    | 0.6534 | 0.6791 | 0.9735   |
| 0.0061        | 30.0  | 870  | 0.1827          | 0.7004    | 0.6614 | 0.6803 | 0.9735   |
| 0.0061        | 31.0  | 899  | 0.1850          | 0.7014    | 0.6175 | 0.6568 | 0.9719   |
| 0.0061        | 32.0  | 928  | 0.1842          | 0.7072    | 0.6255 | 0.6638 | 0.9724   |


### 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": "prueba1", "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 

prueba1
=======


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: 0.1842
* Precision: 0.7072
* Recall: 0.6255
* F1: 0.6638
* Accuracy: 0.9724


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: 3.5e-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: 3.5e-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: 3.5e-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: 3.5e-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