| | --- |
| | license: apache-2.0 |
| | tags: |
| | - image-classification |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - recall |
| | - f1 |
| | - precision |
| | model-index: |
| | - name: vit-base-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-base-modified-augmented-ph2-patch-16 |
| |
|
| | This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the ahishamm/Modified_Augmented_PH2_db_sharpened dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0010 |
| | - Accuracy: 1.0 |
| | - Recall: 1.0 |
| | - F1: 1.0 |
| | - Precision: 1.0 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| |
| | | 0.1238 | 0.29 | 50 | 0.1973 | 0.9332 | 0.9332 | 0.9332 | 0.9332 | |
| | | 0.1857 | 0.59 | 100 | 0.1084 | 0.9623 | 0.9623 | 0.9623 | 0.9623 | |
| | | 0.2506 | 0.88 | 150 | 0.0773 | 0.9692 | 0.9692 | 0.9692 | 0.9692 | |
| | | 0.0247 | 1.18 | 200 | 0.1158 | 0.9606 | 0.9606 | 0.9606 | 0.9606 | |
| | | 0.0089 | 1.47 | 250 | 0.0162 | 0.9914 | 0.9914 | 0.9914 | 0.9914 | |
| | | 0.0226 | 1.76 | 300 | 0.0020 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.0261 | 2.06 | 350 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.0014 | 2.35 | 400 | 0.0014 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.0012 | 2.65 | 450 | 0.0013 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.0013 | 2.94 | 500 | 0.0012 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.0011 | 3.24 | 550 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.001 | 3.53 | 600 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.0011 | 3.82 | 650 | 0.0010 | 1.0 | 1.0 | 1.0 | 1.0 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.30.2 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.13.1 |
| | - Tokenizers 0.13.3 |
| |
|
