| | --- |
| | license: apache-2.0 |
| | tags: |
| | - image-classification |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - recall |
| | - f1 |
| | - precision |
| | model-index: |
| | - name: vit-large-modified-augmented-ph2-patch-16 |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # vit-large-modified-augmented-ph2-patch-16 |
| |
|
| | This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](https://huggingface.co/google/vit-large-patch16-224-in21k) on the ahishamm/Modified_Augmented_PH2_db_sharpened dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0827 |
| | - Accuracy: 0.9709 |
| | - Recall: 0.9709 |
| | - F1: 0.9709 |
| | - Precision: 0.9709 |
| |
|
| | ## 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: |
| | - learning_rate: 0.0002 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 4 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | F1 | Precision | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| |
| | | 0.3402 | 0.29 | 50 | 0.6269 | 0.7945 | 0.7945 | 0.7945 | 0.7945 | |
| | | 0.1387 | 0.59 | 100 | 0.2957 | 0.8921 | 0.8921 | 0.8921 | 0.8921 | |
| | | 0.2921 | 0.88 | 150 | 0.3157 | 0.8836 | 0.8836 | 0.8836 | 0.8836 | |
| | | 0.1268 | 1.18 | 200 | 0.4557 | 0.8527 | 0.8527 | 0.8527 | 0.8527 | |
| | | 0.2071 | 1.47 | 250 | 0.2690 | 0.8818 | 0.8818 | 0.8818 | 0.8818 | |
| | | 0.1238 | 1.76 | 300 | 0.2999 | 0.9178 | 0.9178 | 0.9178 | 0.9178 | |
| | | 0.1327 | 2.06 | 350 | 0.6026 | 0.7877 | 0.7877 | 0.7877 | 0.7877 | |
| | | 0.1453 | 2.35 | 400 | 0.2887 | 0.8990 | 0.8990 | 0.8990 | 0.8990 | |
| | | 0.0686 | 2.65 | 450 | 0.2049 | 0.9503 | 0.9503 | 0.9503 | 0.9503 | |
| | | 0.0414 | 2.94 | 500 | 0.3040 | 0.9195 | 0.9195 | 0.9195 | 0.9195 | |
| | | 0.0851 | 3.24 | 550 | 0.2244 | 0.9298 | 0.9298 | 0.9298 | 0.9298 | |
| | | 0.0054 | 3.53 | 600 | 0.1356 | 0.9555 | 0.9555 | 0.9555 | 0.9555 | |
| | | 0.0029 | 3.82 | 650 | 0.0827 | 0.9709 | 0.9709 | 0.9709 | 0.9709 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.30.2 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.13.1 |
| | - Tokenizers 0.13.3 |
| |
|
