---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Negation_Scope_Detection_NubEs_Training_Development_mBERT_fine_tuned
  results: []

widget:

- text: "Paciente con diagnóstico de ELA en abril de 2015 que presenta desde hace más de dos meses disfagia progresiva, para líquidos preferentemente, con dos neumonías por aspiración, por lo que se programa ingreso para colocación de sonda de gastrostomía, realizándose el día 31 de diciembre, sin complicaciones y tolerando posteriormente la dieta por gastrostomía."
---

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# Negation_Scope_Detection_NubEs_Training_Development_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 + Development) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1712
- Precision: 0.8970
- Recall: 0.9177
- F1: 0.9072
- Accuracy: 0.9722

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1805        | 1.0   | 1726  | 0.1542          | 0.8408    | 0.8600 | 0.8503 | 0.9591   |
| 0.126         | 2.0   | 3452  | 0.1271          | 0.8652    | 0.8774 | 0.8713 | 0.9640   |
| 0.0814        | 3.0   | 5178  | 0.1395          | 0.8715    | 0.8881 | 0.8797 | 0.9662   |
| 0.0447        | 4.0   | 6904  | 0.1326          | 0.8893    | 0.9068 | 0.8979 | 0.9696   |
| 0.0247        | 5.0   | 8630  | 0.1805          | 0.9012    | 0.9020 | 0.9016 | 0.9708   |
| 0.0156        | 6.0   | 10356 | 0.1524          | 0.8972    | 0.9120 | 0.9045 | 0.9706   |
| 0.0056        | 7.0   | 12082 | 0.1712          | 0.8970    | 0.9177 | 0.9072 | 0.9722   |


### Framework versions

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