---
base_model: dccuchile/bert-base-spanish-wwm-uncased
tags:
- generated_from_keras_callback
model-index:
- name: lulygavri/sub1-wsp
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# lulygavri/sub1-wsp

This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0192
- Validation Loss: 0.2130
- Train Accuracy: 0.9492
- Train Precision: [0.96024845 0.88152174]
- Train Precision W: 0.9478
- Train Recall: [0.98025362 0.78357488]
- Train Recall W: 0.9492
- Train F1: [0.97014792 0.82966752]
- Train F1 W: 0.9480
- Epoch: 5

## 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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 340, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 500, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Train Precision         | Train Precision W | Train Recall            | Train Recall W | Train F1                | Train F1 W | Epoch |
|:----------:|:---------------:|:--------------:|:-----------------------:|:-----------------:|:-----------------------:|:--------------:|:-----------------------:|:----------:|:-----:|
| 0.4028     | 0.2959          | 0.8429         | [0.84274809 1.        ] | 0.8676            | [1.         0.00483092] | 0.8429         | [0.91466446 0.00961538] | 0.7718     | 1     |
| 0.1572     | 0.1686          | 0.9315         | [0.94412331 0.8463357 ] | 0.9287            | [0.97644928 0.69178744] | 0.9315         | [0.96001425 0.76129718] | 0.9286     | 2     |
| 0.1028     | 0.2179          | 0.9222         | [0.92357119 0.90951638] | 0.9214            | [0.98949275 0.56328502] | 0.9222         | [0.95539619 0.69570406] | 0.9144     | 3     |
| 0.0554     | 0.1492          | 0.9475         | [0.96816208 0.83641675] | 0.9474            | [0.96956522 0.82995169] | 0.9475         | [0.96886314 0.83317168] | 0.9474     | 4     |
| 0.0192     | 0.2130          | 0.9492         | [0.96024845 0.88152174] | 0.9478            | [0.98025362 0.78357488] | 0.9492         | [0.97014792 0.82966752] | 0.9480     | 5     |


### Framework versions

- Transformers 4.38.1
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2