---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: gustavokpc/en_MODEL_bert-base-uncased_LRATE_1e-05_EPOCHS_7
  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/en_MODEL_bert-base-uncased_LRATE_1e-05_EPOCHS_7

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: 0.0150
- Train Accuracy: 0.9951
- Train F1 M: 0.5657
- Train Precision M: 0.4067
- Train Recall M: 0.9873
- Validation Loss: 0.1309
- Validation Accuracy: 0.9655
- Validation F1 M: 0.5737
- Validation Precision M: 0.4163
- Validation Recall M: 0.9980
- Epoch: 3

## 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': 1e-05, 'decay_steps': 3962, '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 |
|:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
| 0.1966     | 0.9215         | 0.4030     | 0.3067            | 0.6414         | 0.0842          | 0.9708              | 0.5427          | 0.4013                 | 0.9115              | 0     |
| 0.0631     | 0.9799         | 0.5517     | 0.4014            | 0.9425         | 0.0667          | 0.9726              | 0.5583          | 0.4067                 | 0.9621              | 1     |
| 0.0305     | 0.9912         | 0.5630     | 0.4059            | 0.9778         | 0.0696          | 0.9779              | 0.5517          | 0.4013                 | 0.9580              | 2     |
| 0.0150     | 0.9951         | 0.5657     | 0.4067            | 0.9873         | 0.1309          | 0.9655              | 0.5737          | 0.4163                 | 0.9980              | 3     |


### Framework versions

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