---
license: mit
base_model: badokorach/afriqa_afroxlmr_eng_280124
tags:
- generated_from_keras_callback
model-index:
- name: badokorach/mobilebert-uncased-finetuned-agic-170224
  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-170224

This model is a fine-tuned version of [badokorach/afriqa_afroxlmr_eng_280124](https://huggingface.co/badokorach/afriqa_afroxlmr_eng_280124) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0052
- Validation Loss: 0.0
- Epoch: 4

## 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: {'inner_optimizer': {'module': 'keras.optimizers', 'class_name': 'Adam', 'config': {'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': None, 'class_name': 'CustomLearningRateScheduler', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 2736, 'warmup_steps': 304, 'end_learning_rate': 1e-05}, 'registered_name': 'CustomLearningRateScheduler'}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}, 'registered_name': None}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 1.0244     | 0.0             | 0     |
| 0.0181     | 0.0             | 1     |
| 0.0138     | 0.0             | 2     |
| 0.0053     | 0.0             | 3     |
| 0.0052     | 0.0             | 4     |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.17.0
- Tokenizers 0.15.2