---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: cruiser/final_model
  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. -->

# cruiser/final_model

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: 0.0316
- Validation Loss: 1.1405
- Train Accuracy: 0.7835
- Epoch: 10

## 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': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 1e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 34090, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 250, 'power': 1.0, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.6358     | 0.5405          | 0.7821         | 0     |
| 0.4380     | 0.5118          | 0.7844         | 1     |
| 0.3382     | 0.5437          | 0.7960         | 2     |
| 0.2327     | 0.6227          | 0.7878         | 3     |
| 0.1581     | 0.7234          | 0.7795         | 4     |
| 0.1104     | 0.8340          | 0.7832         | 5     |
| 0.0826     | 0.8824          | 0.7778         | 6     |
| 0.0608     | 1.0342          | 0.7827         | 7     |
| 0.0456     | 1.0815          | 0.7818         | 8     |
| 0.0396     | 1.0829          | 0.7852         | 9     |
| 0.0316     | 1.1405          | 0.7835         | 10    |


### Framework versions

- Transformers 4.27.4
- TensorFlow 2.11.0
- Datasets 2.1.0
- Tokenizers 0.13.2