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

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: 1.3621
- Accuracy: 0.6867
- F1: 0.6845

## 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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 24

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 1.0316        | 1.0   | 1000  | 0.9725          | 0.5383   | 0.5182 |
| 0.8887        | 2.0   | 2000  | 0.8652          | 0.5925   | 0.5901 |
| 0.8132        | 3.0   | 3000  | 0.8327          | 0.6175   | 0.6143 |
| 0.7639        | 4.0   | 4000  | 0.8030          | 0.6367   | 0.6356 |
| 0.7233        | 5.0   | 5000  | 0.7969          | 0.6433   | 0.6408 |
| 0.6977        | 6.0   | 6000  | 0.7848          | 0.6508   | 0.6500 |
| 0.6531        | 7.0   | 7000  | 0.7923          | 0.66     | 0.6590 |
| 0.6149        | 8.0   | 8000  | 0.7879          | 0.6683   | 0.6667 |
| 0.5964        | 9.0   | 9000  | 0.7835          | 0.6708   | 0.6705 |
| 0.5508        | 10.0  | 10000 | 0.8072          | 0.6725   | 0.6701 |
| 0.5288        | 11.0  | 11000 | 0.8277          | 0.665    | 0.6604 |
| 0.4828        | 12.0  | 12000 | 0.8436          | 0.6833   | 0.6810 |
| 0.4457        | 13.0  | 13000 | 0.8679          | 0.6717   | 0.6681 |
| 0.432         | 14.0  | 14000 | 0.8695          | 0.6692   | 0.6679 |
| 0.4128        | 15.0  | 15000 | 0.9217          | 0.6858   | 0.6833 |
| 0.3831        | 16.0  | 16000 | 0.9300          | 0.6733   | 0.6714 |
| 0.3471        | 17.0  | 17000 | 0.9796          | 0.675    | 0.6726 |
| 0.3245        | 18.0  | 18000 | 1.0319          | 0.6742   | 0.6726 |
| 0.3016        | 19.0  | 19000 | 1.0977          | 0.6733   | 0.6692 |
| 0.2702        | 20.0  | 20000 | 1.1130          | 0.6667   | 0.6634 |
| 0.2602        | 21.0  | 21000 | 1.1475          | 0.6758   | 0.6741 |
| 0.2316        | 22.0  | 22000 | 1.2237          | 0.6725   | 0.6694 |
| 0.2176        | 23.0  | 23000 | 1.2664          | 0.6775   | 0.6758 |
| 0.2067        | 24.0  | 24000 | 1.3621          | 0.6867   | 0.6845 |


### Framework versions

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