metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: volvoDon/petro-daemon
results: []
volvoDon/petro-daemon
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on a DataSet of petrologic cross sections. It achieves the following results on the evaluation set:
- Train Loss: 0.8890
- Validation Loss: 1.1803
- Train Accuracy: 0.6
- Epoch: 19
Model description
More information needed
Intended uses & limitations
Currently it is just a proof of concept and does a great job identifiying Olivine It currently is not ready for a production enviroment but the results are promising, with an improved dataset I'm confident better results could be acheived.
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 300, '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}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Train Accuracy | Epoch |
|---|---|---|---|
| 1.6519 | 1.7095 | 0.2 | 0 |
| 1.5905 | 1.6747 | 0.2 | 1 |
| 1.5690 | 1.6342 | 0.2 | 2 |
| 1.5170 | 1.5931 | 0.2 | 3 |
| 1.4764 | 1.5528 | 0.6 | 4 |
| 1.3835 | 1.5079 | 0.6 | 5 |
| 1.3420 | 1.4717 | 0.6 | 6 |
| 1.3171 | 1.4232 | 0.6 | 7 |
| 1.2897 | 1.3905 | 0.6 | 8 |
| 1.2702 | 1.3794 | 0.6 | 9 |
| 1.2023 | 1.3351 | 0.6 | 10 |
| 1.1480 | 1.3384 | 0.6 | 11 |
| 1.1434 | 1.3419 | 0.6 | 12 |
| 1.0499 | 1.3226 | 0.6 | 13 |
| 1.0672 | 1.2647 | 0.6 | 14 |
| 1.0526 | 1.1533 | 0.6 | 15 |
| 1.0184 | 1.1546 | 0.6 | 16 |
| 0.9505 | 1.2491 | 0.6 | 17 |
| 0.9578 | 1.2809 | 0.4 | 18 |
| 0.8890 | 1.1803 | 0.6 | 19 |
Framework versions
- Transformers 4.32.1
- TensorFlow 2.12.0
- Datasets 2.14.4
- Tokenizers 0.13.3