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license: apache-2.0
base_model: google/vit-base-patch16-384
tags:
- generated_from_keras_callback
model-index:
- name: Prahas10/roof-shingles
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. -->
# Prahas10/roof-shingles
This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16-384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1015
- Validation Loss: 0.3231
- Train Accuracy: 0.9083
- Epoch: 29
## 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', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 4e-05, 'decay_steps': 138270, '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': 0.0001}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 3.8367 | 2.9703 | 0.4403 | 0 |
| 1.3092 | 1.6169 | 0.7093 | 1 |
| 0.4529 | 1.4414 | 0.7112 | 2 |
| 0.2229 | 0.8445 | 0.8368 | 3 |
| 0.1451 | 0.7074 | 0.8556 | 4 |
| 0.1053 | 0.8585 | 0.7992 | 5 |
| 0.1175 | 1.0721 | 0.7389 | 6 |
| 0.1388 | 0.5802 | 0.8542 | 7 |
| 0.0647 | 0.3764 | 0.9083 | 8 |
| 0.1049 | 1.0484 | 0.7366 | 9 |
| 0.0740 | 0.6191 | 0.8321 | 10 |
| 0.0816 | 0.6273 | 0.8283 | 11 |
| 0.0981 | 0.2901 | 0.9172 | 12 |
| 0.0614 | 0.5081 | 0.8523 | 13 |
| 0.0548 | 0.4983 | 0.8612 | 14 |
| 0.0652 | 0.8008 | 0.7850 | 15 |
| 0.0857 | 0.5845 | 0.8415 | 16 |
| 0.0847 | 0.6887 | 0.8184 | 17 |
| 0.0645 | 0.6104 | 0.8405 | 18 |
| 0.0891 | 0.4770 | 0.8532 | 19 |
| 0.0532 | 0.5074 | 0.8500 | 20 |
| 0.0483 | 0.8208 | 0.7850 | 21 |
| 0.0498 | 0.2679 | 0.9083 | 22 |
| 0.0406 | 0.3261 | 0.9036 | 23 |
| 0.0578 | 0.6373 | 0.8340 | 24 |
| 0.1010 | 0.5037 | 0.8481 | 25 |
| 0.0583 | 0.2993 | 0.8984 | 26 |
| 0.0398 | 0.1538 | 0.9492 | 27 |
| 0.0492 | 0.4397 | 0.8641 | 28 |
| 0.1015 | 0.3231 | 0.9083 | 29 |
### Framework versions
- Transformers 4.41.1
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1
|