|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_keras_callback |
|
widget: |
|
- src: https://cdn.prod.www.spiegel.de/images/6b1135cd-0001-0004-0000-000000867699_w996_r1.778_fpx50_fpy47.38.jpg |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: philschmid/vit-base-patch16-224-in21k-euroSat |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: eurosat |
|
type: eurosat |
|
args: default |
|
metrics: |
|
- name: accuracy |
|
type: accuracy |
|
value: 0.9906 |
|
- name: top-3-accuracy |
|
type: top-3-accuracy |
|
value: 1.0000 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# philschmid/vit-base-patch16-224-in21k-euroSat |
|
|
|
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Train Loss: 0.0218 |
|
- Train Accuracy: 0.9990 |
|
- Train Top-3-accuracy: 1.0000 |
|
- Validation Loss: 0.0440 |
|
- Validation Accuracy: 0.9906 |
|
- Validation Top-3-accuracy: 1.0 |
|
- Epoch: 5 |
|
|
|
## 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': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 3585, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000} |
|
- training_precision: mixed_float16 |
|
|
|
### Training results |
|
|
|
| Train Loss | Train Accuracy | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch | |
|
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:| |
|
| 0.4692 | 0.9471 | 0.9878 | 0.1455 | 0.9861 | 0.9998 | 1 | |
|
| 0.0998 | 0.9888 | 0.9996 | 0.0821 | 0.9864 | 0.9995 | 2 | |
|
| 0.0517 | 0.9939 | 0.9999 | 0.0617 | 0.9871 | 1.0 | 3 | |
|
| 0.0309 | 0.9971 | 0.9999 | 0.0524 | 0.9878 | 0.9998 | 4 | |
|
| 0.0218 | 0.9990 | 1.0000 | 0.0440 | 0.9906 | 1.0 | 5 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.15.0 |
|
- TensorFlow 2.7.0 |
|
- Datasets 1.17.0 |
|
- Tokenizers 0.10.3 |
|
|
