---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep7_lr1
  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_lr1

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: 0.1449
- Precision: 0.8612
- Recall: 0.8723
- F1: 0.8667
- Accuracy: 0.9764

## 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  | 0.0884          | 0.8278    | 0.8351 | 0.8314 | 0.9737   |
| 0.1032        | 2.0   | 934  | 0.0841          | 0.8327    | 0.8591 | 0.8457 | 0.9739   |
| 0.0556        | 3.0   | 1401 | 0.0941          | 0.8699    | 0.8654 | 0.8677 | 0.9762   |
| 0.0317        | 4.0   | 1868 | 0.1146          | 0.8697    | 0.8654 | 0.8676 | 0.9764   |
| 0.0202        | 5.0   | 2335 | 0.1323          | 0.8736    | 0.8621 | 0.8678 | 0.9767   |
| 0.0114        | 6.0   | 2802 | 0.1385          | 0.8563    | 0.8766 | 0.8663 | 0.9758   |
| 0.0064        | 7.0   | 3269 | 0.1449          | 0.8612    | 0.8723 | 0.8667 | 0.9764   |


### Framework versions

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