File size: 3,879 Bytes
b79f3cc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 | ---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: AlaaHussien/weather_classifier_model2
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. -->
# AlaaHussien/weather_classifier_model2
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: 0.0700
- Validation Loss: 0.2853
- Train Accuracy: 0.9250
- Train Precision: 0.9267
- Train Recall: 0.9250
- Train F1: 0.9248
- Epoch: 19
## 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': 3e-05, 'decay_steps': 109780, '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 | Train Precision | Train Recall | Train F1 | Epoch |
|:----------:|:---------------:|:--------------:|:---------------:|:------------:|:--------:|:-----:|
| 1.2545 | 0.6449 | 0.8944 | 0.9010 | 0.8944 | 0.8907 | 0 |
| 0.5392 | 0.3960 | 0.9177 | 0.9191 | 0.9177 | 0.9181 | 1 |
| 0.3498 | 0.3183 | 0.9264 | 0.9271 | 0.9264 | 0.9263 | 2 |
| 0.2787 | 0.2797 | 0.9323 | 0.9331 | 0.9323 | 0.9323 | 3 |
| 0.2155 | 0.2695 | 0.9257 | 0.9279 | 0.9257 | 0.9260 | 4 |
| 0.1899 | 0.3079 | 0.9126 | 0.9165 | 0.9126 | 0.9121 | 5 |
| 0.1599 | 0.2749 | 0.9235 | 0.9259 | 0.9235 | 0.9241 | 6 |
| 0.1470 | 0.2709 | 0.9243 | 0.9257 | 0.9243 | 0.9237 | 7 |
| 0.1305 | 0.2566 | 0.9257 | 0.9263 | 0.9257 | 0.9259 | 8 |
| 0.1131 | 0.2699 | 0.9257 | 0.9271 | 0.9257 | 0.9260 | 9 |
| 0.1042 | 0.2719 | 0.9228 | 0.9240 | 0.9228 | 0.9229 | 10 |
| 0.0977 | 0.2857 | 0.9199 | 0.9208 | 0.9199 | 0.9197 | 11 |
| 0.0816 | 0.2592 | 0.9279 | 0.9294 | 0.9279 | 0.9281 | 12 |
| 0.0894 | 0.2888 | 0.9228 | 0.9256 | 0.9228 | 0.9226 | 13 |
| 0.1011 | 0.2978 | 0.9264 | 0.9287 | 0.9264 | 0.9264 | 14 |
| 0.0756 | 0.2590 | 0.9330 | 0.9344 | 0.9330 | 0.9330 | 15 |
| 0.0668 | 0.2863 | 0.9228 | 0.9255 | 0.9228 | 0.9235 | 16 |
| 0.0650 | 0.2871 | 0.9264 | 0.9282 | 0.9264 | 0.9262 | 17 |
| 0.0644 | 0.3003 | 0.9257 | 0.9279 | 0.9257 | 0.9261 | 18 |
| 0.0700 | 0.2853 | 0.9250 | 0.9267 | 0.9250 | 0.9248 | 19 |
### Framework versions
- Transformers 4.51.3
- TensorFlow 2.18.0
- Datasets 3.6.0
- Tokenizers 0.21.1
|