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# Negation_Scope_Detection_NubEs_Training_Testing_mBERT_fine_tuned

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on Nubes (Training + Testing) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2020
- Precision: 0.8911
- Recall: 0.9059
- F1: 0.8984
- Accuracy: 0.9696

## 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: 5e-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: 7

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.189         | 1.0   | 1726  | 0.1664          | 0.8333    | 0.8544 | 0.8437 | 0.9591   |
| 0.14          | 2.0   | 3452  | 0.1588          | 0.8548    | 0.8821 | 0.8682 | 0.9598   |
| 0.0866        | 3.0   | 5178  | 0.1497          | 0.8856    | 0.8853 | 0.8854 | 0.9664   |
| 0.0504        | 4.0   | 6904  | 0.1633          | 0.8747    | 0.8965 | 0.8855 | 0.9668   |
| 0.0311        | 5.0   | 8630  | 0.1870          | 0.8942    | 0.8984 | 0.8963 | 0.9689   |
| 0.0147        | 6.0   | 10356 | 0.1913          | 0.8829    | 0.9041 | 0.8934 | 0.9684   |
| 0.007         | 7.0   | 12082 | 0.2020          | 0.8911    | 0.9059 | 0.8984 | 0.9696   |


### 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"], "widget": [{"text": "Paciente con diagn\u00f3stico de ELA en abril de 2015 que presenta desde hace m\u00e1s de dos meses disfagia progresiva, para l\u00edquidos preferentemente, con dos neumon\u00edas por aspiraci\u00f3n, por lo que se programa ingreso para colocaci\u00f3n de sonda de gastrostom\u00eda, realiz\u00e1ndose el d\u00eda 31 de diciembre, sin complicaciones y tolerando posteriormente la dieta por gastrostom\u00eda."}], "model-index": [{"name": "Negation_Scope_Detection_NubEs_Training_Testing_mBERT_fine_tuned", "results": []}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

Negation\_Scope\_Detection\_NubEs\_Training\_Testing\_mBERT\_fine\_tuned
========================================================================


This model is a fine-tuned version of bert-base-multilingual-cased on Nubes (Training + Testing) dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2020
* Precision: 0.8911
* Recall: 0.9059
* F1: 0.8984
* Accuracy: 0.9696


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: 5e-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: 7


### 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: 5e-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: 7 ### 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 #bert #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: 5e-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: 7 ### 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 #bert #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: 5e-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: 7### Training results### Framework versions


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