---
base_model: dccuchile/bert-base-spanish-wwm-uncased
tags:
- generated_from_keras_callback
model-index:
- name: lulygavri/sub1-trans
  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-trans

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: 0.0428
- Validation Loss: 0.4923
- Train Accuracy: 0.9
- Train Precision: [0.90909091 0.        ]
- Train Precision W: 0.8273
- Train Recall: [0.98901099 0.        ]
- Train Recall W: 0.9
- Train F1: [0.94736842 0.        ]
- Train F1 W: 0.8621
- 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': 34, '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 |
|:----------:|:---------------:|:--------------:|:-----------------------:|:-----------------:|:-----------------------:|:--------------:|:-----------------------:|:----------:|:-----:|
| 0.6479     | 0.4942          | 0.91           | [0.91 0.  ]             | 0.8281            | [1. 0.]                 | 0.91           | [0.95287958 0.        ] | 0.8671     | 1     |
| 0.4492     | 0.4305          | 0.8            | [0.9382716  0.21052632] | 0.8728            | [0.83516484 0.44444444] | 0.8            | [0.88372093 0.28571429] | 0.8299     | 2     |
| 0.1358     | 0.3080          | 0.88           | [0.90721649 0.        ] | 0.8256            | [0.96703297 0.        ] | 0.88           | [0.93617021 0.        ] | 0.8519     | 3     |
| 0.0545     | 0.3801          | 0.9            | [0.90909091 0.        ] | 0.8273            | [0.98901099 0.        ] | 0.9            | [0.94736842 0.        ] | 0.8621     | 4     |
| 0.0428     | 0.4923          | 0.9            | [0.90909091 0.        ] | 0.8273            | [0.98901099 0.        ] | 0.9            | [0.94736842 0.        ] | 0.8621     | 5     |


### Framework versions

- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2