---
library_name: transformers
base_model: dccuchile/bert-base-spanish-wwm-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: betoNer-biobert
  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. -->

# betoNer-biobert

This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1179
- Precision: 0.9511
- Recall: 0.9644
- F1: 0.9577
- Accuracy: 0.9773

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 306  | 0.1159          | 0.9263    | 0.9509 | 0.9384 | 0.9686   |
| 0.3168        | 2.0   | 612  | 0.1014          | 0.9358    | 0.9642 | 0.9498 | 0.9742   |
| 0.3168        | 3.0   | 918  | 0.0959          | 0.9462    | 0.9656 | 0.9558 | 0.9767   |
| 0.0777        | 4.0   | 1224 | 0.1011          | 0.9451    | 0.9661 | 0.9555 | 0.9767   |
| 0.0541        | 5.0   | 1530 | 0.1073          | 0.9512    | 0.9643 | 0.9577 | 0.9772   |
| 0.0541        | 6.0   | 1836 | 0.1083          | 0.9441    | 0.9611 | 0.9525 | 0.9751   |
| 0.0385        | 7.0   | 2142 | 0.1100          | 0.9515    | 0.9632 | 0.9573 | 0.9776   |
| 0.0385        | 8.0   | 2448 | 0.1153          | 0.9477    | 0.9658 | 0.9567 | 0.9770   |
| 0.0325        | 9.0   | 2754 | 0.1161          | 0.9495    | 0.9633 | 0.9564 | 0.9769   |
| 0.0255        | 10.0  | 3060 | 0.1179          | 0.9511    | 0.9644 | 0.9577 | 0.9773   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0