---
base_model: dccuchile/bert-base-spanish-wwm-cased
tags:
- generated_from_trainer
metrics:
- f1
- recall
model-index:
- name: bert-base-spanish-wwm-cased_K5
  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-cased_K5

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: 0.0182
- F1 Macro: 0.9973
- F1: 0.9980
- F1 Neg: 0.9966
- Acc: 0.9975
- Prec: 0.9980
- Recall: 0.9980
- Mcc: 0.9946

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1     | F1 Neg | Acc    | Prec   | Recall | Mcc    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:|
| No log        | 1.0   | 400  | 0.0263          | 0.9960   | 0.9970 | 0.9949 | 0.9962 | 0.9980 | 0.9961 | 0.9919 |
| 0.0591        | 2.0   | 800  | 0.0182          | 0.9973   | 0.9980 | 0.9966 | 0.9975 | 0.9980 | 0.9980 | 0.9946 |
| 0.0123        | 3.0   | 1200 | 0.0225          | 0.9973   | 0.9980 | 0.9966 | 0.9975 | 0.9980 | 0.9980 | 0.9946 |
| 0.0078        | 4.0   | 1600 | 0.0227          | 0.9973   | 0.9980 | 0.9966 | 0.9975 | 0.9980 | 0.9980 | 0.9946 |
| 0.002         | 5.0   | 2000 | 0.0229          | 0.9973   | 0.9980 | 0.9966 | 0.9975 | 0.9980 | 0.9980 | 0.9946 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2