| | --- |
| | license: apache-2.0 |
| | base_model: google/vit-base-patch16-224 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - imagefolder |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: vit-base-patch16-224-type |
| | results: |
| | - task: |
| | name: Image Classification |
| | type: image-classification |
| | dataset: |
| | name: imagefolder |
| | type: imagefolder |
| | config: default |
| | split: validation |
| | args: default |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.7423708920187794 |
| | --- |
| | |
| | <!-- 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-patch16-224-type |
| |
|
| | 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: 0.7556 |
| | - Accuracy: 0.7424 |
| |
|
| | ## 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: 3e-05 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 128 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.5461 | 1.0 | 62 | 0.7743 | 0.7230 | |
| | | 0.4924 | 1.99 | 124 | 0.7858 | 0.7248 | |
| | | 0.5121 | 2.99 | 186 | 0.7973 | 0.7330 | |
| | | 0.5216 | 4.0 | 249 | 0.7749 | 0.7289 | |
| | | 0.5788 | 5.0 | 311 | 0.7801 | 0.7312 | |
| | | 0.5863 | 5.99 | 373 | 0.7705 | 0.7424 | |
| | | 0.5862 | 6.99 | 435 | 0.7560 | 0.7424 | |
| | | 0.5327 | 8.0 | 498 | 0.7631 | 0.7365 | |
| | | 0.5155 | 9.0 | 560 | 0.7560 | 0.7406 | |
| | | 0.511 | 9.96 | 620 | 0.7556 | 0.7424 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.34.1 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.14.1 |
| |
|
