---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep9_lr4
  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_ep9_lr4

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: 0.1801
- Precision: 0.6659
- Recall: 0.7266
- F1: 0.6950
- Accuracy: 0.9478

## 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-08
- 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: 9

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 467  | 0.2732          | 0.6635    | 0.6619 | 0.6627 | 0.9415   |
| 0.2772        | 2.0   | 934  | 0.2436          | 0.6562    | 0.6820 | 0.6688 | 0.9426   |
| 0.2379        | 3.0   | 1401 | 0.2224          | 0.6550    | 0.6980 | 0.6758 | 0.9437   |
| 0.2142        | 4.0   | 1868 | 0.2071          | 0.6597    | 0.7104 | 0.6841 | 0.9450   |
| 0.1968        | 5.0   | 2335 | 0.1960          | 0.6597    | 0.7165 | 0.6869 | 0.9461   |
| 0.1888        | 6.0   | 2802 | 0.1884          | 0.6610    | 0.7195 | 0.6890 | 0.9468   |
| 0.1788        | 7.0   | 3269 | 0.1835          | 0.6641    | 0.7244 | 0.6929 | 0.9474   |
| 0.1768        | 8.0   | 3736 | 0.1808          | 0.6652    | 0.7258 | 0.6942 | 0.9477   |
| 0.1695        | 9.0   | 4203 | 0.1801          | 0.6659    | 0.7266 | 0.6950 | 0.9478   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3