---
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- roc_auc
- f1
model-index:
- name: results
  results: []
datasets:
- alecmontero/dataset_tweetsmx_areasCPC
language:
- es
library_name: transformers
---

<!-- 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. -->

# results

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1516
- Roc Auc: 0.8130
- Hamming Loss: 0.0509
- F1 Score: 0.6969
- Accuracy: 0.4418
- Precision: 0.8279
- Recall: 0.6583

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Roc Auc | Hamming Loss | F1 Score | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------------:|:--------:|:--------:|:---------:|:------:|
| No log        | 1.0   | 374  | 0.2285          | 0.6386  | 0.0822       | 0.3390   | 0.2731   | 0.8932    | 0.3080 |
| 0.2678        | 2.0   | 748  | 0.1870          | 0.7175  | 0.0679       | 0.5123   | 0.3481   | 0.7842    | 0.4679 |
| 0.1722        | 3.0   | 1122 | 0.1727          | 0.7839  | 0.0607       | 0.6116   | 0.3949   | 0.7611    | 0.6096 |
| 0.1722        | 4.0   | 1496 | 0.1577          | 0.7865  | 0.0545       | 0.6408   | 0.4137   | 0.8178    | 0.6096 |
| 0.1236        | 5.0   | 1870 | 0.1537          | 0.8055  | 0.0523       | 0.6798   | 0.4230   | 0.8250    | 0.6423 |
| 0.0847        | 6.0   | 2244 | 0.1570          | 0.8069  | 0.0541       | 0.6695   | 0.4297   | 0.7839    | 0.6503 |
| 0.063         | 7.0   | 2618 | 0.1516          | 0.8130  | 0.0509       | 0.6969   | 0.4418   | 0.8279    | 0.6583 |
| 0.063         | 8.0   | 2992 | 0.1531          | 0.8147  | 0.0512       | 0.6856   | 0.4458   | 0.7982    | 0.6622 |
| 0.0465        | 9.0   | 3366 | 0.1526          | 0.8427  | 0.0489       | 0.7544   | 0.4565   | 0.8190    | 0.7174 |
| 0.0349        | 10.0  | 3740 | 0.1534          | 0.8349  | 0.0498       | 0.7414   | 0.4431   | 0.8212    | 0.7023 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1