---
license: mit
base_model: csarron/mobilebert-uncased-squad-v2
tags:
- generated_from_keras_callback
model-index:
- name: badokorach/mobilebert-uncased-finetuned-agic-060124
  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/mobilebert-uncased-finetuned-agic-060124

This model is a fine-tuned version of [csarron/mobilebert-uncased-squad-v2](https://huggingface.co/csarron/mobilebert-uncased-squad-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.4106
- Validation Loss: 0.0
- 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': 0.02, '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': 1e-05, 'decay_steps': 1160, 'end_learning_rate': 1e-07, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 2.4542     | 0.0             | 0     |
| 2.0632     | 0.0             | 1     |
| 1.8930     | 0.0             | 2     |
| 1.7858     | 0.0             | 3     |
| 1.6640     | 0.0             | 4     |
| 1.5885     | 0.0             | 5     |
| 1.5269     | 0.0             | 6     |
| 1.4618     | 0.0             | 7     |
| 1.4648     | 0.0             | 8     |
| 1.4106     | 0.0             | 9     |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.0