---
base_model: mrm8488/bert-small-finetuned-squadv2
tags:
- generated_from_keras_callback
model-index:
- name: badokorach/bert-finetuned-270124
  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. -->

# badokorach/bert-finetuned-270124

This model is a fine-tuned version of [mrm8488/bert-small-finetuned-squadv2](https://huggingface.co/mrm8488/bert-small-finetuned-squadv2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.5643
- Validation Loss: 0.0
- Epoch: 13

## 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 2190, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.02}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 1.6716     | 0.0             | 0     |
| 1.3976     | 0.0             | 1     |
| 1.2882     | 0.0             | 2     |
| 1.1789     | 0.0             | 3     |
| 1.0754     | 0.0             | 4     |
| 1.0056     | 0.0             | 5     |
| 0.9075     | 0.0             | 6     |
| 0.8294     | 0.0             | 7     |
| 0.7633     | 0.0             | 8     |
| 0.7044     | 0.0             | 9     |
| 0.6744     | 0.0             | 10    |
| 0.6376     | 0.0             | 11    |
| 0.5851     | 0.0             | 12    |
| 0.5643     | 0.0             | 13    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.1