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

# FNST_trad_j

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: 2.6540
- Accuracy: 0.6525
- F1: 0.6178

## 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-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: 32

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 1.1058        | 1.0   | 1500  | 1.0564          | 0.5442   | 0.3843 |
| 0.9559        | 2.0   | 3000  | 0.9522          | 0.585    | 0.5503 |
| 0.8789        | 3.0   | 4500  | 0.8843          | 0.61     | 0.5733 |
| 0.8292        | 4.0   | 6000  | 0.8614          | 0.6167   | 0.5734 |
| 0.7807        | 5.0   | 7500  | 0.8519          | 0.62     | 0.5896 |
| 0.7559        | 6.0   | 9000  | 0.8648          | 0.6283   | 0.5965 |
| 0.7098        | 7.0   | 10500 | 0.8579          | 0.63     | 0.5961 |
| 0.6703        | 8.0   | 12000 | 0.8536          | 0.6417   | 0.6029 |
| 0.6114        | 9.0   | 13500 | 0.8686          | 0.6358   | 0.5997 |
| 0.611         | 10.0  | 15000 | 0.8948          | 0.6342   | 0.6045 |
| 0.5614        | 11.0  | 16500 | 0.9173          | 0.6342   | 0.6046 |
| 0.515         | 12.0  | 18000 | 0.9289          | 0.6425   | 0.6089 |
| 0.5107        | 13.0  | 19500 | 0.9581          | 0.64     | 0.6052 |
| 0.4691        | 14.0  | 21000 | 1.0099          | 0.6433   | 0.6091 |
| 0.4476        | 15.0  | 22500 | 1.0543          | 0.6458   | 0.6108 |
| 0.398         | 16.0  | 24000 | 1.1170          | 0.6425   | 0.6051 |
| 0.3828        | 17.0  | 25500 | 1.1585          | 0.6517   | 0.6102 |
| 0.3567        | 18.0  | 27000 | 1.2252          | 0.6475   | 0.6114 |
| 0.3334        | 19.0  | 28500 | 1.2827          | 0.6675   | 0.6317 |
| 0.2982        | 20.0  | 30000 | 1.4256          | 0.6517   | 0.6257 |
| 0.2734        | 21.0  | 31500 | 1.4591          | 0.6583   | 0.6305 |
| 0.2556        | 22.0  | 33000 | 1.5516          | 0.66     | 0.6263 |
| 0.2409        | 23.0  | 34500 | 1.6793          | 0.6592   | 0.6219 |
| 0.2226        | 24.0  | 36000 | 1.8157          | 0.66     | 0.6218 |
| 0.1971        | 25.0  | 37500 | 1.9089          | 0.6575   | 0.6241 |
| 0.1832        | 26.0  | 39000 | 2.0406          | 0.6558   | 0.6300 |
| 0.1921        | 27.0  | 40500 | 2.1448          | 0.6583   | 0.6254 |
| 0.1496        | 28.0  | 42000 | 2.2888          | 0.6458   | 0.6136 |
| 0.1538        | 29.0  | 43500 | 2.3520          | 0.66     | 0.6241 |
| 0.1558        | 30.0  | 45000 | 2.4748          | 0.6492   | 0.6207 |
| 0.1409        | 31.0  | 46500 | 2.5126          | 0.6542   | 0.6175 |
| 0.119         | 32.0  | 48000 | 2.6540          | 0.6525   | 0.6178 |


### Framework versions

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