---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: modelBeto6
  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. -->

# modelBeto6

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: 0.1808
- Precision: 0.6219
- Recall: 0.6545
- F1: 0.6378
- Accuracy: 0.9737

## 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: 6e-05
- train_batch_size: 32
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 29   | 0.2309          | 0.0       | 0.0    | 0.0    | 0.9440   |
| No log        | 2.0   | 58   | 0.2034          | 0.0       | 0.0    | 0.0    | 0.9440   |
| No log        | 3.0   | 87   | 0.1685          | 0.1429    | 0.0157 | 0.0283 | 0.9476   |
| No log        | 4.0   | 116  | 0.1425          | 0.3034    | 0.1414 | 0.1929 | 0.9546   |
| No log        | 5.0   | 145  | 0.1285          | 0.3802    | 0.2408 | 0.2949 | 0.9589   |
| No log        | 6.0   | 174  | 0.1283          | 0.5922    | 0.3194 | 0.4150 | 0.9696   |
| No log        | 7.0   | 203  | 0.1337          | 0.5630    | 0.3979 | 0.4663 | 0.9715   |
| No log        | 8.0   | 232  | 0.1184          | 0.5505    | 0.6283 | 0.5868 | 0.9686   |
| No log        | 9.0   | 261  | 0.1308          | 0.5882    | 0.5759 | 0.5820 | 0.9729   |
| No log        | 10.0  | 290  | 0.1329          | 0.5989    | 0.5550 | 0.5761 | 0.9729   |
| No log        | 11.0  | 319  | 0.1549          | 0.6781    | 0.5183 | 0.5875 | 0.9742   |
| No log        | 12.0  | 348  | 0.1578          | 0.6221    | 0.5602 | 0.5895 | 0.9732   |
| No log        | 13.0  | 377  | 0.1505          | 0.6117    | 0.6021 | 0.6069 | 0.9716   |
| No log        | 14.0  | 406  | 0.1671          | 0.6412    | 0.5707 | 0.6039 | 0.9729   |
| No log        | 15.0  | 435  | 0.1684          | 0.5902    | 0.5654 | 0.5775 | 0.9710   |
| No log        | 16.0  | 464  | 0.1707          | 0.6216    | 0.6021 | 0.6117 | 0.9727   |
| No log        | 17.0  | 493  | 0.1715          | 0.6453    | 0.5812 | 0.6116 | 0.9737   |
| 0.0738        | 18.0  | 522  | 0.1729          | 0.5734    | 0.6545 | 0.6112 | 0.9701   |
| 0.0738        | 19.0  | 551  | 0.1815          | 0.5990    | 0.6021 | 0.6005 | 0.9716   |
| 0.0738        | 20.0  | 580  | 0.1746          | 0.6354    | 0.6387 | 0.6371 | 0.9732   |
| 0.0738        | 21.0  | 609  | 0.1654          | 0.6686    | 0.5916 | 0.6278 | 0.9749   |
| 0.0738        | 22.0  | 638  | 0.1678          | 0.6359    | 0.6492 | 0.6425 | 0.9741   |
| 0.0738        | 23.0  | 667  | 0.1704          | 0.6218    | 0.6283 | 0.625  | 0.9742   |
| 0.0738        | 24.0  | 696  | 0.1746          | 0.6685    | 0.6440 | 0.6560 | 0.9747   |
| 0.0738        | 25.0  | 725  | 0.1772          | 0.6224    | 0.6387 | 0.6305 | 0.9739   |
| 0.0738        | 26.0  | 754  | 0.1792          | 0.6484    | 0.6178 | 0.6327 | 0.9741   |
| 0.0738        | 27.0  | 783  | 0.1788          | 0.6383    | 0.6283 | 0.6332 | 0.9741   |
| 0.0738        | 28.0  | 812  | 0.1802          | 0.6281    | 0.6545 | 0.6410 | 0.9741   |
| 0.0738        | 29.0  | 841  | 0.1803          | 0.6443    | 0.6545 | 0.6494 | 0.9747   |
| 0.0738        | 30.0  | 870  | 0.1804          | 0.6495    | 0.6597 | 0.6545 | 0.9749   |
| 0.0738        | 31.0  | 899  | 0.1805          | 0.6443    | 0.6545 | 0.6494 | 0.9746   |
| 0.0738        | 32.0  | 928  | 0.1808          | 0.6219    | 0.6545 | 0.6378 | 0.9737   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3