
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# testlink

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: 0.2031
- Precision: 0.5065
- Recall: 0.6359
- F1: 0.5639
- Accuracy: 0.9658

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 57   | 0.2133          | 0.0       | 0.0    | 0.0    | 0.9516   |
| No log        | 2.0   | 114  | 0.1757          | 0.2       | 0.0163 | 0.0302 | 0.9550   |
| No log        | 3.0   | 171  | 0.1591          | 0.2893    | 0.1902 | 0.2295 | 0.9535   |
| No log        | 4.0   | 228  | 0.1386          | 0.3433    | 0.25   | 0.2893 | 0.9582   |
| No log        | 5.0   | 285  | 0.1349          | 0.4345    | 0.3967 | 0.4148 | 0.9600   |
| No log        | 6.0   | 342  | 0.1311          | 0.5352    | 0.4130 | 0.4663 | 0.9646   |
| No log        | 7.0   | 399  | 0.1402          | 0.4264    | 0.5978 | 0.4977 | 0.9590   |
| No log        | 8.0   | 456  | 0.1377          | 0.4858    | 0.5598 | 0.5202 | 0.9634   |
| 0.1282        | 9.0   | 513  | 0.1539          | 0.5226    | 0.4402 | 0.4779 | 0.9651   |
| 0.1282        | 10.0  | 570  | 0.1631          | 0.4597    | 0.6196 | 0.5278 | 0.9607   |
| 0.1282        | 11.0  | 627  | 0.1511          | 0.5333    | 0.4783 | 0.5043 | 0.9666   |
| 0.1282        | 12.0  | 684  | 0.1705          | 0.4690    | 0.5761 | 0.5171 | 0.9626   |
| 0.1282        | 13.0  | 741  | 0.1760          | 0.5138    | 0.5054 | 0.5096 | 0.9651   |
| 0.1282        | 14.0  | 798  | 0.1917          | 0.4296    | 0.6630 | 0.5214 | 0.9580   |
| 0.1282        | 15.0  | 855  | 0.1833          | 0.4563    | 0.625  | 0.5275 | 0.9619   |
| 0.1282        | 16.0  | 912  | 0.1887          | 0.4933    | 0.6033 | 0.5428 | 0.9638   |
| 0.1282        | 17.0  | 969  | 0.1723          | 0.5138    | 0.6087 | 0.5572 | 0.9659   |
| 0.0102        | 18.0  | 1026 | 0.1849          | 0.5022    | 0.6196 | 0.5547 | 0.9649   |
| 0.0102        | 19.0  | 1083 | 0.1773          | 0.5352    | 0.6196 | 0.5743 | 0.9676   |
| 0.0102        | 20.0  | 1140 | 0.1945          | 0.4957    | 0.6304 | 0.5550 | 0.9646   |
| 0.0102        | 21.0  | 1197 | 0.1967          | 0.4756    | 0.6359 | 0.5442 | 0.9634   |
| 0.0102        | 22.0  | 1254 | 0.1876          | 0.4978    | 0.6087 | 0.5477 | 0.9658   |
| 0.0102        | 23.0  | 1311 | 0.1935          | 0.4978    | 0.6087 | 0.5477 | 0.9656   |
| 0.0102        | 24.0  | 1368 | 0.1930          | 0.5256    | 0.6141 | 0.5664 | 0.9671   |
| 0.0102        | 25.0  | 1425 | 0.1945          | 0.5110    | 0.6304 | 0.5645 | 0.9661   |
| 0.0102        | 26.0  | 1482 | 0.1955          | 0.5283    | 0.6087 | 0.5657 | 0.9673   |
| 0.0023        | 27.0  | 1539 | 0.2017          | 0.5043    | 0.6359 | 0.5625 | 0.9654   |
| 0.0023        | 28.0  | 1596 | 0.2010          | 0.5088    | 0.6304 | 0.5631 | 0.9659   |
| 0.0023        | 29.0  | 1653 | 0.2019          | 0.5088    | 0.6304 | 0.5631 | 0.9659   |
| 0.0023        | 30.0  | 1710 | 0.2031          | 0.5065    | 0.6359 | 0.5639 | 0.9658   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

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

testlink
========


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: 0.2031
* Precision: 0.5065
* Recall: 0.6359
* F1: 0.5639
* Accuracy: 0.9658


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: 30


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### 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: 30 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
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: 30 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
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: 30### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3