---
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_keras_callback
model-index:
- name: gustavokpc/IC_11
  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_11

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: 0.1200
- Train Accuracy: 0.9569
- Train F1 M: 0.5414
- Train Precision M: 0.3981
- Train Recall M: 0.9034
- Validation Loss: 0.2290
- Validation Accuracy: 0.9202
- Validation F1 M: 0.5513
- Validation Precision M: 0.4022
- Validation Recall M: 0.9261
- Epoch: 6

## 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-06, 'decay_steps': 5306, '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 |
|:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
| 0.4434     | 0.8014         | 0.4236     | 0.3661            | 0.5865         | 0.2743          | 0.8872              | 0.4964          | 0.3787                 | 0.7644              | 0     |
| 0.2804     | 0.8901         | 0.4898     | 0.3778            | 0.7488         | 0.2824          | 0.8879              | 0.5567          | 0.4181                 | 0.8782              | 1     |
| 0.2254     | 0.9128         | 0.5069     | 0.3838            | 0.8028         | 0.2388          | 0.9090              | 0.5468          | 0.4009                 | 0.9053              | 2     |
| 0.1873     | 0.9303         | 0.5203     | 0.3889            | 0.8490         | 0.2200          | 0.9149              | 0.5561          | 0.4075                 | 0.9235              | 3     |
| 0.1614     | 0.9404         | 0.5316     | 0.3944            | 0.8756         | 0.2188          | 0.9235              | 0.5566          | 0.4080                 | 0.9242              | 4     |
| 0.1380     | 0.9497         | 0.5359     | 0.3956            | 0.8898         | 0.2205          | 0.9228              | 0.5506          | 0.4024                 | 0.9213              | 5     |
| 0.1200     | 0.9569         | 0.5414     | 0.3981            | 0.9034         | 0.2290          | 0.9202              | 0.5513          | 0.4022                 | 0.9261              | 6     |


### Framework versions

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