
<!-- 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. -->

# Xanadu00/galaxy_classifier_mobilevit_3

This model is a fine-tuned version of [apple/mobilevit-small](https://huggingface.co/apple/mobilevit-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1914
- Train Accuracy: 0.9341
- Validation Loss: 0.5148
- Validation Accuracy: 0.8512
- Epoch: 16

## 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': 'AdamW', 'weight_decay': 0.01, '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': {'class_name': 'ExponentialDecay', 'config': {'initial_learning_rate': 0.002, 'decay_steps': 10000, 'decay_rate': 0.01, 'staircase': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 1.1049     | 0.6128         | 0.7422          | 0.7517              | 0     |
| 0.7149     | 0.7564         | 0.6376          | 0.7821              | 1     |
| 0.6080     | 0.7945         | 0.6947          | 0.7745              | 2     |
| 0.5376     | 0.8160         | 0.5589          | 0.8134              | 3     |
| 0.4977     | 0.8279         | 0.5458          | 0.8162              | 4     |
| 0.4564     | 0.8407         | 0.4799          | 0.8441              | 5     |
| 0.4271     | 0.8557         | 0.4765          | 0.8413              | 6     |
| 0.3957     | 0.8619         | 0.4790          | 0.8453              | 7     |
| 0.3701     | 0.8741         | 0.5376          | 0.8329              | 8     |
| 0.3425     | 0.8829         | 0.4359          | 0.8619              | 9     |
| 0.3192     | 0.8892         | 0.4475          | 0.8585              | 10    |
| 0.2972     | 0.8967         | 0.4143          | 0.8712              | 11    |
| 0.2691     | 0.9080         | 0.4819          | 0.8498              | 12    |
| 0.2445     | 0.9144         | 0.4543          | 0.8563              | 13    |
| 0.2261     | 0.9220         | 0.4221          | 0.8689              | 14    |
| 0.2127     | 0.9251         | 0.5076          | 0.8540              | 15    |
| 0.1914     | 0.9341         | 0.5148          | 0.8512              | 16    |


### Framework versions

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

barred spiral cigar round smooth distributed edge-on with bulge edge-on without bulge in-between round smooth merging round smooth unbarred loss spiral unbarred tight spiral