pytorch tensorboard bert token-classification transformers generated_from_trainer license:apache-2.0 model-index autotrain_compatible
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NLP-CIC-WFU_SocialDisNER_fine_tuned_NER_EHR_Spanish_model_Mulitlingual_BERT_v2
  results: []
---

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# NLP-CIC-WFU_SocialDisNER_fine_tuned_NER_EHR_Spanish_model_Mulitlingual_BERT_v2

This model is a fine-tuned version of [ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT](https://huggingface.co/ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1483
- Precision: 0.8699
- Recall: 0.8722
- F1: 0.8711
- Accuracy: 0.9771

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 467  | 0.0851          | 0.8415    | 0.8209 | 0.8310 | 0.9720   |
| 0.1011        | 2.0   | 934  | 0.1034          | 0.8681    | 0.8464 | 0.8571 | 0.9744   |
| 0.0537        | 3.0   | 1401 | 0.1094          | 0.8527    | 0.8608 | 0.8568 | 0.9753   |
| 0.0335        | 4.0   | 1868 | 0.1239          | 0.8617    | 0.8603 | 0.8610 | 0.9751   |
| 0.0185        | 5.0   | 2335 | 0.1192          | 0.8689    | 0.8627 | 0.8658 | 0.9756   |
| 0.0112        | 6.0   | 2802 | 0.1426          | 0.8672    | 0.8663 | 0.8667 | 0.9765   |
| 0.0067        | 7.0   | 3269 | 0.1483          | 0.8699    | 0.8722 | 0.8711 | 0.9771   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
