---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: MUmairAB/bert-ner
  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. -->

# MUmairAB/bert-ner

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0003
- Validation Loss: 0.0880
- Epoch: 18

## 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 17560, '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, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 0.1775     | 0.0635          | 0     |
| 0.0470     | 0.0559          | 1     |
| 0.0278     | 0.0603          | 2     |
| 0.0174     | 0.0603          | 3     |
| 0.0124     | 0.0615          | 4     |
| 0.0077     | 0.0722          | 5     |
| 0.0060     | 0.0731          | 6     |
| 0.0038     | 0.0757          | 7     |
| 0.0043     | 0.0731          | 8     |
| 0.0041     | 0.0735          | 9     |
| 0.0019     | 0.0724          | 10    |
| 0.0019     | 0.0786          | 11    |
| 0.0010     | 0.0843          | 12    |
| 0.0008     | 0.0814          | 13    |
| 0.0011     | 0.0867          | 14    |
| 0.0008     | 0.0883          | 15    |
| 0.0005     | 0.0861          | 16    |
| 0.0005     | 0.0869          | 17    |
| 0.0003     | 0.0880          | 18    |


### Framework versions

- Transformers 4.30.2
- TensorFlow 2.12.0
- Datasets 2.13.1
- Tokenizers 0.13.3