---
license: other
base_model: apple/mobilevit-xx-small
tags:
- generated_from_keras_callback
model-index:
- name: hafizurUMaine/cifar10_m
  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. -->

# hafizurUMaine/cifar10_m

This model is a fine-tuned version of [apple/mobilevit-xx-small](https://huggingface.co/apple/mobilevit-xx-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.0094
- Train Accuracy: 0.7334
- Validation Loss: 0.9668
- Validation Accuracy: 0.7490
- 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: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 400000, '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': 0.01}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 5.5748     | 0.1482         | 3.1655          | 0.4160              | 0     |
| 2.4468     | 0.5135         | 1.7772          | 0.6195              | 1     |
| 1.5927     | 0.6389         | 1.3152          | 0.6770              | 2     |
| 1.2333     | 0.7001         | 1.1226          | 0.7265              | 3     |
| 1.0094     | 0.7334         | 0.9668          | 0.7490              | 4     |


### Framework versions

- Transformers 4.37.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.1