---
base_model: dccuchile/bert-base-spanish-wwm-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: ABL_trad_k
  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. -->

# ABL_trad_k

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: 2.8641
- Accuracy: 0.6842
- F1: 0.6826

## 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: 1e-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: 36

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.9411        | 1.0   | 1500  | 0.9017          | 0.5792   | 0.5764 |
| 0.8328        | 2.0   | 3000  | 0.8458          | 0.62     | 0.6188 |
| 0.8006        | 3.0   | 4500  | 0.8183          | 0.64     | 0.6391 |
| 0.7283        | 4.0   | 6000  | 0.8154          | 0.6442   | 0.6430 |
| 0.7006        | 5.0   | 7500  | 0.7978          | 0.6492   | 0.6487 |
| 0.6555        | 6.0   | 9000  | 0.8009          | 0.6542   | 0.6536 |
| 0.6263        | 7.0   | 10500 | 0.8033          | 0.6617   | 0.6612 |
| 0.5805        | 8.0   | 12000 | 0.8155          | 0.6658   | 0.6657 |
| 0.5385        | 9.0   | 13500 | 0.8608          | 0.675    | 0.6729 |
| 0.5108        | 10.0  | 15000 | 0.8545          | 0.6733   | 0.6732 |
| 0.4791        | 11.0  | 16500 | 0.8950          | 0.6758   | 0.6750 |
| 0.4423        | 12.0  | 18000 | 0.9145          | 0.6792   | 0.6790 |
| 0.4295        | 13.0  | 19500 | 0.9497          | 0.6708   | 0.6707 |
| 0.3782        | 14.0  | 21000 | 1.0309          | 0.6742   | 0.6734 |
| 0.3656        | 15.0  | 22500 | 1.0706          | 0.6783   | 0.6774 |
| 0.3312        | 16.0  | 24000 | 1.1327          | 0.6733   | 0.6730 |
| 0.3008        | 17.0  | 25500 | 1.1870          | 0.6825   | 0.6822 |
| 0.2851        | 18.0  | 27000 | 1.3284          | 0.685    | 0.6847 |
| 0.2636        | 19.0  | 28500 | 1.4260          | 0.6858   | 0.6851 |
| 0.2752        | 20.0  | 30000 | 1.4733          | 0.6833   | 0.6833 |
| 0.2231        | 21.0  | 31500 | 1.6163          | 0.68     | 0.6800 |
| 0.2052        | 22.0  | 33000 | 1.7674          | 0.6792   | 0.6786 |
| 0.198         | 23.0  | 34500 | 1.8474          | 0.6833   | 0.6827 |
| 0.1854        | 24.0  | 36000 | 1.9509          | 0.6775   | 0.6766 |
| 0.1944        | 25.0  | 37500 | 2.0660          | 0.68     | 0.6790 |
| 0.1649        | 26.0  | 39000 | 2.1718          | 0.6825   | 0.6812 |
| 0.1443        | 27.0  | 40500 | 2.3664          | 0.68     | 0.6791 |
| 0.1251        | 28.0  | 42000 | 2.4144          | 0.6833   | 0.6827 |
| 0.1357        | 29.0  | 43500 | 2.4407          | 0.6875   | 0.6875 |
| 0.1279        | 30.0  | 45000 | 2.4419          | 0.6933   | 0.6932 |
| 0.1112        | 31.0  | 46500 | 2.5989          | 0.6833   | 0.6828 |
| 0.098         | 32.0  | 48000 | 2.6390          | 0.68     | 0.6792 |
| 0.0864        | 33.0  | 49500 | 2.7293          | 0.6792   | 0.6780 |
| 0.0897        | 34.0  | 51000 | 2.7814          | 0.6833   | 0.6820 |
| 0.0869        | 35.0  | 52500 | 2.8468          | 0.68     | 0.6787 |
| 0.0834        | 36.0  | 54000 | 2.8641          | 0.6842   | 0.6826 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1