metadata
license: other
tags:
- generated_from_keras_callback
model-index:
- name: Xanadu00/galaxy_classifier
results: []
Xanadu00/galaxy_classifier_mobilevit
This model is a fine-tuned version of apple/mobilevit-small on Galaxy10 DECals dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.3550
- Train Accuracy: 0.8797
- Validation Loss: 0.5428
- Validation Accuracy: 0.8326
- Epoch: 14
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
Dataset Fields
The dataset has the following fields (also called "features"):
{
"image": "Image(decode=True, id=None)",
"target": "ClassLabel(names=['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'], id=['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'])"
}
Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
| Split name | Num samples |
|---|---|
| train | 14188 |
| valid | 3548 |
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: {'name': 'AdamW', 'weight_decay': 0.004, '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': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.002, 'decay_steps': 10000, 'end_learning_rate': 2e-05, 'power': 0.5, 'cycle': 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 |
|---|---|---|---|---|
| 0.9179 | 0.6833 | 0.7849 | 0.7342 | 0 |
| 0.6763 | 0.7702 | 0.7576 | 0.7556 | 1 |
| 0.6042 | 0.7912 | 0.5977 | 0.7909 | 2 |
| 0.5604 | 0.8063 | 0.5499 | 0.8117 | 3 |
| 0.5176 | 0.8213 | 0.5738 | 0.8114 | 4 |
| 0.4944 | 0.8353 | 0.5317 | 0.8176 | 5 |
| 0.4735 | 0.8368 | 0.6051 | 0.7914 | 6 |
| 0.4427 | 0.8483 | 0.5357 | 0.8275 | 7 |
| 0.4430 | 0.8480 | 0.5327 | 0.8250 | 8 |
| 0.4127 | 0.8596 | 0.4947 | 0.8362 | 9 |
| 0.4017 | 0.8603 | 0.5378 | 0.8162 | 10 |
| 0.3840 | 0.8694 | 0.5070 | 0.8326 | 11 |
| 0.3677 | 0.8722 | 0.4875 | 0.8295 | 12 |
| 0.3606 | 0.8778 | 0.5071 | 0.8360 | 13 |
| 0.3550 | 0.8797 | 0.5428 | 0.8326 | 14 |
Framework versions
- Transformers 4.30.2
- TensorFlow 2.12.0
- Datasets 2.13.1
- Tokenizers 0.13.3