---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: bertbaseuncasedny
  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. -->

# bertbaseuncasedny

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: 0.3901
- Train End Logits Accuracy: 0.8823
- Train Start Logits Accuracy: 0.8513
- Validation Loss: 1.2123
- Validation End Logits Accuracy: 0.7291
- Validation Start Logits Accuracy: 0.6977
- 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': 2e-05, 'decay_steps': 29508, '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 End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 1.2597     | 0.6683                    | 0.6277                      | 1.0151          | 0.7214                         | 0.6860                           | 0     |
| 0.7699     | 0.7820                    | 0.7427                      | 1.0062          | 0.7342                         | 0.6996                           | 1     |
| 0.5343     | 0.8425                    | 0.8064                      | 1.1162          | 0.7321                         | 0.7010                           | 2     |
| 0.3901     | 0.8823                    | 0.8513                      | 1.2123          | 0.7291                         | 0.6977                           | 3     |


### Framework versions

- Transformers 4.20.1
- TensorFlow 2.6.4
- Datasets 2.1.0
- Tokenizers 0.12.1