| --- |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: Fine-Tuned_Model3 |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.608 |
| - name: F1 |
| type: f1 |
| value: 0.5096170704866357 |
| --- |
| |
| <!-- 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. --> |
|
|
| # Fine-Tuned_Model3 |
| |
| This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7362 |
| - Accuracy: 0.608 |
| - F1: 0.5096 |
| |
| ## 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: 5e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 30 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | 3.2255 | 5.0 | 20 | 1.9574 | 0.512 | 0.3083 | |
| | 1.3773 | 10.0 | 40 | 0.8854 | 0.584 | 0.4617 | |
| | 0.869 | 15.0 | 60 | 0.7880 | 0.608 | 0.4795 | |
| | 0.7966 | 20.0 | 80 | 0.7732 | 0.6 | 0.4846 | |
| | 0.8458 | 25.0 | 100 | 0.7795 | 0.576 | 0.4112 | |
| | 0.8135 | 30.0 | 120 | 0.7362 | 0.608 | 0.5096 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.37.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.17.0 |
| - Tokenizers 0.15.1 |
| |
