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# prueba4

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: 0.2044
- Precision: 0.7288
- Recall: 0.6853
- F1: 0.7064
- Accuracy: 0.9752

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 57   | 0.2361          | 0.6504    | 0.6892 | 0.6692 | 0.9694   |
| No log        | 2.0   | 114  | 0.2441          | 0.6190    | 0.6733 | 0.6450 | 0.9671   |
| No log        | 3.0   | 171  | 0.2064          | 0.6013    | 0.7211 | 0.6558 | 0.9699   |
| No log        | 4.0   | 228  | 0.2241          | 0.7004    | 0.6335 | 0.6653 | 0.9720   |
| No log        | 5.0   | 285  | 0.1992          | 0.6578    | 0.6892 | 0.6732 | 0.9727   |
| No log        | 6.0   | 342  | 0.2149          | 0.6073    | 0.7331 | 0.6643 | 0.9694   |
| No log        | 7.0   | 399  | 0.2099          | 0.7466    | 0.6574 | 0.6992 | 0.9755   |
| No log        | 8.0   | 456  | 0.2039          | 0.7293    | 0.6653 | 0.6958 | 0.9747   |
| 0.0017        | 9.0   | 513  | 0.2185          | 0.7342    | 0.6494 | 0.6892 | 0.9742   |
| 0.0017        | 10.0  | 570  | 0.2074          | 0.688     | 0.6853 | 0.6866 | 0.9732   |
| 0.0017        | 11.0  | 627  | 0.2010          | 0.7073    | 0.6932 | 0.7002 | 0.9745   |
| 0.0017        | 12.0  | 684  | 0.2030          | 0.7126    | 0.7012 | 0.7068 | 0.9749   |
| 0.0017        | 13.0  | 741  | 0.2045          | 0.7173    | 0.6773 | 0.6967 | 0.9745   |
| 0.0017        | 14.0  | 798  | 0.2040          | 0.7185    | 0.6813 | 0.6994 | 0.9747   |
| 0.0017        | 15.0  | 855  | 0.2044          | 0.7288    | 0.6853 | 0.7064 | 0.9752   |


### 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": "prueba4", "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 

prueba4
=======


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: 0.2044
* Precision: 0.7288
* Recall: 0.6853
* F1: 0.7064
* Accuracy: 0.9752


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: 15


### 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: 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: 15 ### 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: 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: 15 ### 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: 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: 15### Training results### Framework versions


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