---
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_keras_callback
model-index:
- name: gustavokpc/IC_sexto
  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_sexto

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0832
- Train Accuracy: 0.9695
- Train F1 M: 0.5509
- Train Precision M: 0.4007
- Train Recall M: 0.9444
- Validation Loss: 0.2387
- Validation Accuracy: 0.9248
- Validation F1 M: 0.5604
- Validation Precision M: 0.4074
- Validation Recall M: 0.9461
- 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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3790, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, '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 |
|:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
| 0.3898     | 0.8294         | 0.3411     | 0.2894            | 0.4810         | 0.2440          | 0.8984              | 0.5087          | 0.3814                 | 0.8079              | 0     |
| 0.2070     | 0.9228         | 0.4927     | 0.3723            | 0.7869         | 0.1911          | 0.9268              | 0.5222          | 0.3853                 | 0.8520              | 1     |
| 0.1392     | 0.9467         | 0.5266     | 0.3881            | 0.8670         | 0.2310          | 0.9057              | 0.5617          | 0.4162                 | 0.9092              | 2     |
| 0.1136     | 0.9570         | 0.5387     | 0.3946            | 0.9100         | 0.2265          | 0.9228              | 0.5653          | 0.4119                 | 0.9501              | 3     |
| 0.0832     | 0.9695         | 0.5509     | 0.4007            | 0.9444         | 0.2387          | 0.9248              | 0.5604          | 0.4074                 | 0.9461              | 4     |


### Framework versions

- Transformers 4.34.1
- TensorFlow 2.10.0
- Datasets 2.14.5
- Tokenizers 0.14.1