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# WL_DISEASE_NER_v1

This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es) on the wl-disease dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1489
- Diso Precision: 0.7908
- Diso Recall: 0.8397
- Diso F1: 0.8145
- Diso Number: 1765
- Overall Precision: 0.7908
- Overall Recall: 0.8397
- Overall F1: 0.8145
- Overall Accuracy: 0.9631

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Diso Precision | Diso Recall | Diso F1 | Diso Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:-----------:|:-------:|:-----------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.1199        | 1.0   | 1714 | 0.1187          | 0.7739         | 0.7972      | 0.7854  | 1765        | 0.7739            | 0.7972         | 0.7854     | 0.9610           |
| 0.0916        | 2.0   | 3428 | 0.1237          | 0.7748         | 0.8266      | 0.7999  | 1765        | 0.7748            | 0.8266         | 0.7999     | 0.9620           |
| 0.0625        | 3.0   | 5142 | 0.1343          | 0.7900         | 0.8289      | 0.8090  | 1765        | 0.7900            | 0.8289         | 0.8090     | 0.9630           |
| 0.0485        | 4.0   | 6856 | 0.1489          | 0.7908         | 0.8397      | 0.8145  | 1765        | 0.7908            | 0.8397         | 0.8145     | 0.9631           |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["wl-disease"], "model-index": [{"name": "WL_DISEASE_NER_v1", "results": []}]}
transformers pytorch tensorboard roberta token-classification generated_from_trainer dataset:wl-disease license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #dataset-wl-disease #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

WL\_DISEASE\_NER\_v1
====================


This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es on the wl-disease dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1489
* Diso Precision: 0.7908
* Diso Recall: 0.8397
* Diso F1: 0.8145
* Diso Number: 1765
* Overall Precision: 0.7908
* Overall Recall: 0.8397
* Overall F1: 0.8145
* Overall Accuracy: 0.9631


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: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4


### Training results



### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #dataset-wl-disease #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #dataset-wl-disease #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4### Training results### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2