---
base_model: dccuchile/bert-base-spanish-wwm-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: ABL_trad_i
  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_i

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: 3.0155
- Accuracy: 0.6617
- F1: 0.6598

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.9418        | 1.0   | 1500  | 0.9131          | 0.56     | 0.5590 |
| 0.8318        | 2.0   | 3000  | 0.8578          | 0.5992   | 0.5948 |
| 0.7796        | 3.0   | 4500  | 0.8415          | 0.6075   | 0.6057 |
| 0.7139        | 4.0   | 6000  | 0.8327          | 0.6342   | 0.6325 |
| 0.6883        | 5.0   | 7500  | 0.8430          | 0.6333   | 0.6299 |
| 0.6643        | 6.0   | 9000  | 0.8444          | 0.635    | 0.6323 |
| 0.6042        | 7.0   | 10500 | 0.8497          | 0.6483   | 0.6459 |
| 0.5765        | 8.0   | 12000 | 0.8747          | 0.6425   | 0.6407 |
| 0.5301        | 9.0   | 13500 | 0.8833          | 0.6575   | 0.6559 |
| 0.5077        | 10.0  | 15000 | 0.9306          | 0.6575   | 0.6554 |
| 0.492         | 11.0  | 16500 | 0.9494          | 0.6658   | 0.6635 |
| 0.4244        | 12.0  | 18000 | 1.0017          | 0.6642   | 0.6622 |
| 0.3911        | 13.0  | 19500 | 1.0697          | 0.6692   | 0.6673 |
| 0.3965        | 14.0  | 21000 | 1.0836          | 0.6692   | 0.6678 |
| 0.3384        | 15.0  | 22500 | 1.1778          | 0.67     | 0.6682 |
| 0.3142        | 16.0  | 24000 | 1.2995          | 0.6658   | 0.6630 |
| 0.2783        | 17.0  | 25500 | 1.3573          | 0.6667   | 0.6643 |
| 0.2599        | 18.0  | 27000 | 1.4730          | 0.6683   | 0.6672 |
| 0.2553        | 19.0  | 28500 | 1.5837          | 0.6667   | 0.6639 |
| 0.2359        | 20.0  | 30000 | 1.7285          | 0.655    | 0.6525 |
| 0.2237        | 21.0  | 31500 | 1.8383          | 0.6633   | 0.6622 |
| 0.1855        | 22.0  | 33000 | 1.9797          | 0.6625   | 0.6610 |
| 0.2178        | 23.0  | 34500 | 2.0590          | 0.6658   | 0.6637 |
| 0.1607        | 24.0  | 36000 | 2.1819          | 0.6608   | 0.6583 |
| 0.1495        | 25.0  | 37500 | 2.3356          | 0.6583   | 0.6564 |
| 0.1384        | 26.0  | 39000 | 2.4443          | 0.6617   | 0.6603 |
| 0.1638        | 27.0  | 40500 | 2.5224          | 0.6608   | 0.6585 |
| 0.121         | 28.0  | 42000 | 2.6157          | 0.6692   | 0.6671 |
| 0.1288        | 29.0  | 43500 | 2.7674          | 0.6692   | 0.6671 |
| 0.0821        | 30.0  | 45000 | 2.8365          | 0.6658   | 0.6651 |
| 0.0907        | 31.0  | 46500 | 2.9559          | 0.6542   | 0.6512 |
| 0.0821        | 32.0  | 48000 | 3.0155          | 0.6617   | 0.6598 |


### Framework versions

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