---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep7_lr2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# BERT_ep7_lr2

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: 0.0921
- Precision: 0.8435
- Recall: 0.8668
- F1: 0.8550
- Accuracy: 0.9757

## 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-06
- 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  | 0.0875          | 0.8131    | 0.8272 | 0.8201 | 0.9712   |
| 0.1124        | 2.0   | 934  | 0.0855          | 0.8073    | 0.8649 | 0.8351 | 0.9728   |
| 0.075         | 3.0   | 1401 | 0.0824          | 0.8359    | 0.8579 | 0.8467 | 0.9754   |
| 0.0603        | 4.0   | 1868 | 0.0835          | 0.8409    | 0.8587 | 0.8497 | 0.9754   |
| 0.0474        | 5.0   | 2335 | 0.0886          | 0.8428    | 0.8695 | 0.8560 | 0.9755   |
| 0.0434        | 6.0   | 2802 | 0.0899          | 0.8450    | 0.8682 | 0.8565 | 0.9758   |
| 0.0391        | 7.0   | 3269 | 0.0921          | 0.8435    | 0.8668 | 0.8550 | 0.9757   |


### Framework versions

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