---
license: apache-2.0
base_model: google-bert/bert-base-cased
tags:
- generated_from_keras_callback
model-index:
- name: riftz112/school_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. -->

# riftz112/school_model

This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 4.1874
- Validation Loss: 4.0652
- Epoch: 9

## 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 66, '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 | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 5.1114     | 4.3701          | 0     |
| 4.3325     | 4.0652          | 1     |
| 4.1721     | 4.0652          | 2     |
| 4.1802     | 4.0652          | 3     |
| 4.1787     | 4.0652          | 4     |
| 4.1819     | 4.0652          | 5     |
| 4.1785     | 4.0652          | 6     |
| 4.1795     | 4.0652          | 7     |
| 4.1803     | 4.0652          | 8     |
| 4.1874     | 4.0652          | 9     |


### Framework versions

- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1