| --- |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224 |
| tags: |
| - generated_from_keras_callback |
| model-index: |
| - name: TirathP/vit-base-patch16-224-finetuned-customData |
| 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. --> |
|
|
| # TirathP/vit-base-patch16-224-finetuned-customData |
|
|
| This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Train Loss: 0.2775 |
| - Validation Loss: 0.3297 |
| - Validation Accuracy: 0.8571 |
| - 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': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} |
| - training_precision: float32 |
|
|
| ### Training results |
|
|
| | Train Loss | Validation Loss | Validation Accuracy | Epoch | |
| |:----------:|:---------------:|:-------------------:|:-----:| |
| | 1.1397 | 1.0223 | 0.5714 | 0 | |
| | 0.8312 | 0.8338 | 0.5714 | 1 | |
| | 0.7131 | 0.7099 | 0.5714 | 2 | |
| | 0.5754 | 0.6120 | 0.7143 | 3 | |
| | 0.4804 | 0.5374 | 0.7143 | 4 | |
| | 0.3934 | 0.4630 | 0.8571 | 5 | |
| | 0.4258 | 0.3979 | 0.8571 | 6 | |
| | 0.3739 | 0.3455 | 1.0 | 7 | |
| | 0.3143 | 0.2909 | 1.0 | 8 | |
| | 0.3113 | 0.2572 | 0.8571 | 9 | |
| | 0.3327 | 0.2623 | 0.8571 | 10 | |
| | 0.2227 | 0.2993 | 0.8571 | 11 | |
| | 0.2860 | 0.3299 | 0.8571 | 12 | |
| | 0.2081 | 0.3553 | 0.8571 | 13 | |
| | 0.2243 | 0.3360 | 0.8571 | 14 | |
| | 0.2246 | 0.2942 | 0.8571 | 15 | |
| | 0.2570 | 0.2131 | 0.8571 | 16 | |
| | 0.3173 | 0.1850 | 0.8571 | 17 | |
| | 0.1572 | 0.2134 | 0.8571 | 18 | |
| | 0.2775 | 0.3297 | 0.8571 | 19 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.31.0 |
| - TensorFlow 2.12.0 |
| - Datasets 2.14.4 |
| - Tokenizers 0.13.3 |
|
|
