---
base_model: dccuchile/bert-base-spanish-wwm-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bert-base-spanish-wwm-uncased-finetuned-political_elsalvadore
  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-base-spanish-wwm-uncased-finetuned-political_elsalvadore

This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3034
- Accuracy: 0.78
- F1: 0.7796
- Precision: 0.7794
- Recall: 0.78

## 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 66   | 0.6370          | 0.7156   | 0.7164 | 0.7237    | 0.7156 |
| 0.62          | 2.0   | 132  | 0.6332          | 0.7356   | 0.7342 | 0.7333    | 0.7356 |
| 0.62          | 3.0   | 198  | 0.7050          | 0.7356   | 0.7383 | 0.7488    | 0.7356 |
| 0.2306        | 4.0   | 264  | 0.8853          | 0.7356   | 0.7339 | 0.7330    | 0.7356 |
| 0.2306        | 5.0   | 330  | 1.0291          | 0.7244   | 0.7260 | 0.7300    | 0.7244 |
| 0.0704        | 6.0   | 396  | 1.1888          | 0.7333   | 0.7360 | 0.7416    | 0.7333 |
| 0.0704        | 7.0   | 462  | 1.3355          | 0.72     | 0.7245 | 0.7376    | 0.72   |
| 0.0225        | 8.0   | 528  | 1.3803          | 0.7444   | 0.7465 | 0.7500    | 0.7444 |
| 0.0225        | 9.0   | 594  | 1.4822          | 0.7267   | 0.7303 | 0.7415    | 0.7267 |
| 0.0108        | 10.0  | 660  | 1.4441          | 0.7333   | 0.7353 | 0.7386    | 0.7333 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1