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# prueba2

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: 0.1829
- Precision: 0.7232
- Recall: 0.6454
- F1: 0.6821
- Accuracy: 0.9744

## 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: 3e-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   | 0.1726          | 0.7014    | 0.5896 | 0.6407 | 0.9720   |
| No log        | 2.0   | 58   | 0.1712          | 0.6090    | 0.6454 | 0.6267 | 0.9679   |
| No log        | 3.0   | 87   | 0.1665          | 0.6746    | 0.6773 | 0.6759 | 0.9720   |
| No log        | 4.0   | 116  | 0.1945          | 0.7042    | 0.5976 | 0.6466 | 0.9719   |
| No log        | 5.0   | 145  | 0.1850          | 0.6927    | 0.6016 | 0.6439 | 0.9724   |
| No log        | 6.0   | 174  | 0.1872          | 0.6570    | 0.6335 | 0.6450 | 0.9697   |
| No log        | 7.0   | 203  | 0.2014          | 0.7527    | 0.5578 | 0.6407 | 0.9730   |
| No log        | 8.0   | 232  | 0.1696          | 0.6706    | 0.6733 | 0.6720 | 0.9727   |
| No log        | 9.0   | 261  | 0.1743          | 0.6820    | 0.6494 | 0.6653 | 0.9730   |
| No log        | 10.0  | 290  | 0.1686          | 0.6735    | 0.6574 | 0.6653 | 0.9730   |
| No log        | 11.0  | 319  | 0.1868          | 0.6934    | 0.5857 | 0.6350 | 0.9712   |
| No log        | 12.0  | 348  | 0.1930          | 0.7089    | 0.6016 | 0.6509 | 0.9727   |
| No log        | 13.0  | 377  | 0.1826          | 0.7087    | 0.6494 | 0.6778 | 0.9730   |
| No log        | 14.0  | 406  | 0.1920          | 0.7103    | 0.6056 | 0.6538 | 0.9722   |
| No log        | 15.0  | 435  | 0.1848          | 0.6402    | 0.6733 | 0.6563 | 0.9712   |
| No log        | 16.0  | 464  | 0.1843          | 0.6822    | 0.6414 | 0.6612 | 0.9734   |
| No log        | 17.0  | 493  | 0.1874          | 0.7009    | 0.6255 | 0.6611 | 0.9730   |
| 0.0016        | 18.0  | 522  | 0.1844          | 0.6736    | 0.6494 | 0.6613 | 0.9730   |
| 0.0016        | 19.0  | 551  | 0.1850          | 0.7273    | 0.6375 | 0.6794 | 0.9744   |
| 0.0016        | 20.0  | 580  | 0.1737          | 0.7179    | 0.6693 | 0.6928 | 0.9749   |
| 0.0016        | 21.0  | 609  | 0.1798          | 0.7376    | 0.6494 | 0.6907 | 0.9747   |
| 0.0016        | 22.0  | 638  | 0.1797          | 0.7174    | 0.6574 | 0.6861 | 0.9739   |
| 0.0016        | 23.0  | 667  | 0.1783          | 0.7046    | 0.6653 | 0.6844 | 0.9742   |
| 0.0016        | 24.0  | 696  | 0.1784          | 0.7301    | 0.6574 | 0.6918 | 0.9745   |
| 0.0016        | 25.0  | 725  | 0.1818          | 0.7352    | 0.6414 | 0.6851 | 0.9745   |
| 0.0016        | 26.0  | 754  | 0.1823          | 0.7419    | 0.6414 | 0.6880 | 0.9745   |
| 0.0016        | 27.0  | 783  | 0.1786          | 0.7205    | 0.6574 | 0.6875 | 0.9749   |
| 0.0016        | 28.0  | 812  | 0.1781          | 0.7051    | 0.6574 | 0.6804 | 0.9734   |
| 0.0016        | 29.0  | 841  | 0.1802          | 0.7181    | 0.6494 | 0.6820 | 0.9744   |
| 0.0016        | 30.0  | 870  | 0.1801          | 0.7174    | 0.6574 | 0.6861 | 0.9749   |
| 0.0016        | 31.0  | 899  | 0.1824          | 0.7232    | 0.6454 | 0.6821 | 0.9745   |
| 0.0016        | 32.0  | 928  | 0.1829          | 0.7232    | 0.6454 | 0.6821 | 0.9744   |


### 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": "prueba2", "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 

prueba2
=======


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: 0.1829
* Precision: 0.7232
* Recall: 0.6454
* F1: 0.6821
* Accuracy: 0.9744


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: 3e-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: 3e-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: 3e-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: 3e-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