---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: gustavokpc/IC_segundo
  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. -->

# gustavokpc/IC_segundo

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0559
- Train Accuracy: 0.9805
- Train F1 M: 0.5583
- Train Precision M: 0.4028
- Train Recall M: 0.9686
- Validation Loss: 0.2533
- Validation Accuracy: 0.9327
- Validation F1 M: 0.5605
- Validation Precision M: 0.4028
- Validation Recall M: 0.9674
- Epoch: 4

## 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': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 3790, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Train F1 M | Train Precision M | Train Recall M | Validation Loss | Validation Accuracy | Validation F1 M | Validation Precision M | Validation Recall M | Epoch |
|:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
| 0.3576     | 0.8399         | 0.4604     | 0.3607            | 0.7042         | 0.2825          | 0.8997              | 0.5635          | 0.4127                 | 0.9300              | 0     |
| 0.2012     | 0.9274         | 0.5204     | 0.3849            | 0.8616         | 0.2103          | 0.9175              | 0.5451          | 0.3970                 | 0.9095              | 1     |
| 0.1312     | 0.9511         | 0.5451     | 0.3969            | 0.9273         | 0.2125          | 0.9307              | 0.5571          | 0.4017                 | 0.9523              | 2     |
| 0.0871     | 0.9690         | 0.5547     | 0.4007            | 0.9557         | 0.2417          | 0.9301              | 0.5565          | 0.4013                 | 0.9547              | 3     |
| 0.0559     | 0.9805         | 0.5583     | 0.4028            | 0.9686         | 0.2533          | 0.9327              | 0.5605          | 0.4028                 | 0.9674              | 4     |


### Framework versions

- Transformers 4.34.1
- TensorFlow 2.14.0
- Datasets 2.14.5
- Tokenizers 0.14.1