| | --- |
| | license: apache-2.0 |
| | base_model: google/vit-base-patch16-224-in21k |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - imagefolder |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: image_classification |
| | 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: 0.4375 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # image_classification |
| | |
| | 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 imagefolder dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.5566 |
| | - Accuracy: 0.4375 |
| | |
| | ## 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: 1e-05 |
| | - train_batch_size: 15 |
| | - eval_batch_size: 15 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 15 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | No log | 1.0 | 43 | 2.0423 | 0.2562 | |
| | | No log | 2.0 | 86 | 1.9764 | 0.2812 | |
| | | No log | 3.0 | 129 | 1.8803 | 0.3125 | |
| | | No log | 4.0 | 172 | 1.7690 | 0.3187 | |
| | | No log | 5.0 | 215 | 1.6910 | 0.375 | |
| | | No log | 6.0 | 258 | 1.6397 | 0.3688 | |
| | | No log | 7.0 | 301 | 1.6053 | 0.4688 | |
| | | No log | 8.0 | 344 | 1.5674 | 0.4875 | |
| | | No log | 9.0 | 387 | 1.5714 | 0.4625 | |
| | | No log | 10.0 | 430 | 1.5394 | 0.4938 | |
| | | No log | 11.0 | 473 | 1.5183 | 0.4375 | |
| | | 1.6941 | 12.0 | 516 | 1.5211 | 0.4938 | |
| | | 1.6941 | 13.0 | 559 | 1.4997 | 0.4562 | |
| | | 1.6941 | 14.0 | 602 | 1.5191 | 0.4375 | |
| | | 1.6941 | 15.0 | 645 | 1.4892 | 0.4875 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.33.2 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.13.3 |
| | |
