---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep5_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_ep5_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: 0.0922
- Precision: 0.8259
- Recall: 0.8778
- F1: 0.8511
- Accuracy: 0.9740

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 467  | 0.0878          | 0.7978    | 0.8576 | 0.8266 | 0.9708   |
| 0.1112        | 2.0   | 934  | 0.0861          | 0.8072    | 0.8780 | 0.8411 | 0.9718   |
| 0.0746        | 3.0   | 1401 | 0.0867          | 0.8212    | 0.8756 | 0.8475 | 0.9736   |
| 0.0586        | 4.0   | 1868 | 0.0901          | 0.8239    | 0.8780 | 0.8501 | 0.9737   |
| 0.0539        | 5.0   | 2335 | 0.0922          | 0.8259    | 0.8778 | 0.8511 | 0.9740   |


### Framework versions

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