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# testlink-class-2

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: 0.2116
- Precision: 0.7516
- Recall: 0.6901
- F1: 0.7195
- Accuracy: 0.9758

## 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: 7.5e-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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 29   | 0.2388          | 0.7315    | 0.6374 | 0.6813 | 0.9739   |
| No log        | 2.0   | 58   | 0.1956          | 0.6169    | 0.7251 | 0.6667 | 0.9723   |
| No log        | 3.0   | 87   | 0.1637          | 0.6302    | 0.7076 | 0.6667 | 0.9730   |
| No log        | 4.0   | 116  | 0.2107          | 0.6810    | 0.6491 | 0.6647 | 0.9741   |
| No log        | 5.0   | 145  | 0.1987          | 0.6981    | 0.6491 | 0.6727 | 0.9745   |
| No log        | 6.0   | 174  | 0.1524          | 0.7355    | 0.6667 | 0.6994 | 0.9756   |
| No log        | 7.0   | 203  | 0.1933          | 0.7664    | 0.6140 | 0.6818 | 0.9750   |
| No log        | 8.0   | 232  | 0.2150          | 0.7836    | 0.6140 | 0.6885 | 0.9747   |
| No log        | 9.0   | 261  | 0.1700          | 0.7405    | 0.6842 | 0.7112 | 0.9761   |
| No log        | 10.0  | 290  | 0.1626          | 0.6142    | 0.7076 | 0.6576 | 0.9730   |
| No log        | 11.0  | 319  | 0.1826          | 0.7035    | 0.7076 | 0.7055 | 0.9761   |
| No log        | 12.0  | 348  | 0.1724          | 0.6802    | 0.6842 | 0.6822 | 0.9758   |
| No log        | 13.0  | 377  | 0.1823          | 0.7852    | 0.6199 | 0.6928 | 0.9741   |
| No log        | 14.0  | 406  | 0.1833          | 0.7284    | 0.6901 | 0.7087 | 0.9761   |
| No log        | 15.0  | 435  | 0.1816          | 0.5853    | 0.7427 | 0.6546 | 0.9701   |
| No log        | 16.0  | 464  | 0.2084          | 0.7770    | 0.6725 | 0.7210 | 0.9761   |
| No log        | 17.0  | 493  | 0.2043          | 0.7069    | 0.7193 | 0.7130 | 0.9748   |
| 0.0022        | 18.0  | 522  | 0.1996          | 0.6541    | 0.7076 | 0.6798 | 0.9741   |
| 0.0022        | 19.0  | 551  | 0.2013          | 0.7484    | 0.6959 | 0.7212 | 0.9763   |
| 0.0022        | 20.0  | 580  | 0.1933          | 0.7159    | 0.7368 | 0.7262 | 0.9770   |
| 0.0022        | 21.0  | 609  | 0.1931          | 0.7101    | 0.7018 | 0.7059 | 0.9759   |
| 0.0022        | 22.0  | 638  | 0.1946          | 0.7052    | 0.7135 | 0.7093 | 0.9759   |
| 0.0022        | 23.0  | 667  | 0.1968          | 0.6936    | 0.7018 | 0.6977 | 0.9752   |
| 0.0022        | 24.0  | 696  | 0.2076          | 0.7296    | 0.6784 | 0.7030 | 0.9754   |
| 0.0022        | 25.0  | 725  | 0.2076          | 0.7296    | 0.6784 | 0.7030 | 0.9756   |
| 0.0022        | 26.0  | 754  | 0.2051          | 0.6941    | 0.6901 | 0.6921 | 0.9747   |
| 0.0022        | 27.0  | 783  | 0.2106          | 0.7342    | 0.6784 | 0.7052 | 0.9752   |
| 0.0022        | 28.0  | 812  | 0.2093          | 0.7312    | 0.6842 | 0.7069 | 0.9752   |
| 0.0022        | 29.0  | 841  | 0.2112          | 0.7516    | 0.6901 | 0.7195 | 0.9758   |
| 0.0022        | 30.0  | 870  | 0.2116          | 0.7516    | 0.6901 | 0.7195 | 0.9758   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "testlink-class-2", "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-class-2
================


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: 0.2116
* Precision: 0.7516
* Recall: 0.6901
* F1: 0.7195
* Accuracy: 0.9758


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: 7.5e-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: 30


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-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: 30 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* 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: 7.5e-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: 30 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3