| | --- |
| | 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 |
| | |
