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

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: 0.1339
- Train Accuracy: 0.9523
- Train F1 M: 0.5559
- Train Precision M: 0.4041
- Train Recall M: 0.9513
- Validation Loss: 0.2110
- Validation Accuracy: 0.9222
- Validation F1 M: 0.5681
- Validation Precision M: 0.4137
- Validation Recall M: 0.9574
- Epoch: 2

## 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': 2274, '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 |
|:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
| 0.4176     | 0.8080         | 0.4543     | 0.3667            | 0.6857         | 0.2600          | 0.8991              | 0.5567          | 0.4108                 | 0.9084              | 0     |
| 0.2122     | 0.9203         | 0.5400     | 0.3991            | 0.8908         | 0.2049          | 0.9215              | 0.5529          | 0.4068                 | 0.9089              | 1     |
| 0.1339     | 0.9523         | 0.5559     | 0.4041            | 0.9513         | 0.2110          | 0.9222              | 0.5681          | 0.4137                 | 0.9574              | 2     |


### Framework versions

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