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

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: 0.2648
- Validation Loss: 0.2302
- Train Accuracy: 0.8400
- Train Precision: [0.9935821  0.39460253]
- Train Precision W: 0.9301
- Train Recall: [0.82643237 0.95494063]
- Train Recall W: 0.8400
- Train F1: [0.90233174 0.55844377]
- Train F1 W: 0.8659
- Epoch: 1

## 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': 18106, '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: mixed_float16

### Training results

| Train Loss | Validation Loss | Train Accuracy | Train Precision         | Train Precision W | Train Recall            | Train Recall W | Train F1                | Train F1 W | Epoch |
|:----------:|:---------------:|:--------------:|:-----------------------:|:-----------------:|:-----------------------:|:--------------:|:-----------------------:|:----------:|:-----:|
| 0.2648     | 0.2302          | 0.8400         | [0.9935821  0.39460253] | 0.9301            | [0.82643237 0.95494063] | 0.8400         | [0.90233174 0.55844377] | 0.8659     | 1     |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.1