|
|
--- |
|
|
license: apache-2.0 |
|
|
base_model: google/vit-base-patch16-224-in21k |
|
|
tags: |
|
|
- generated_from_keras_callback |
|
|
model-index: |
|
|
- name: arieg/spec_cls_80_v2 |
|
|
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. --> |
|
|
|
|
|
# arieg/spec_cls_80_v2 |
|
|
|
|
|
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: 1.0698 |
|
|
- Validation Loss: 1.0517 |
|
|
- Train Accuracy: 1.0 |
|
|
- Epoch: 9 |
|
|
|
|
|
## 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', 'clipnorm': 1.0, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 14400, '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 | Validation Loss | Train Accuracy | Epoch | |
|
|
|:----------:|:---------------:|:--------------:|:-----:| |
|
|
| 4.2243 | 4.0115 | 0.575 | 0 | |
|
|
| 3.6964 | 3.4678 | 0.9125 | 1 | |
|
|
| 3.1703 | 2.9932 | 0.9938 | 2 | |
|
|
| 2.7155 | 2.5826 | 0.9938 | 3 | |
|
|
| 2.3313 | 2.2229 | 1.0 | 4 | |
|
|
| 2.0025 | 1.9208 | 1.0 | 5 | |
|
|
| 1.7153 | 1.6639 | 1.0 | 6 | |
|
|
| 1.4721 | 1.4462 | 1.0 | 7 | |
|
|
| 1.2586 | 1.2279 | 1.0 | 8 | |
|
|
| 1.0698 | 1.0517 | 1.0 | 9 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.35.0 |
|
|
- TensorFlow 2.14.0 |
|
|
- Datasets 2.14.6 |
|
|
- Tokenizers 0.14.1 |
|
|
|