| ---
|
| 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-RX1-24
|
| 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: 0.8431372549019608
|
| ---
|
|
|
| <!-- 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-RX1-24
|
|
|
| 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: 0.5687
|
| - Accuracy: 0.8431
|
|
|
| ## 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: 5.5e-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: 0.05
|
| - num_epochs: 24
|
|
|
| ### Training results
|
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| |:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| | No log | 0.93 | 7 | 1.3485 | 0.4706 |
|
| | 1.3674 | 2.0 | 15 | 1.2284 | 0.5490 |
|
| | 1.2414 | 2.93 | 22 | 1.1307 | 0.6471 |
|
| | 1.1146 | 4.0 | 30 | 1.0230 | 0.6471 |
|
| | 1.1146 | 4.93 | 37 | 0.9251 | 0.6863 |
|
| | 0.9522 | 6.0 | 45 | 0.9122 | 0.6471 |
|
| | 0.8247 | 6.93 | 52 | 0.9374 | 0.6275 |
|
| | 0.6825 | 8.0 | 60 | 0.8320 | 0.6863 |
|
| | 0.6825 | 8.93 | 67 | 0.8286 | 0.6667 |
|
| | 0.6191 | 10.0 | 75 | 0.8418 | 0.6667 |
|
| | 0.5312 | 10.93 | 82 | 0.7836 | 0.8235 |
|
| | 0.454 | 12.0 | 90 | 0.7356 | 0.8039 |
|
| | 0.454 | 12.93 | 97 | 0.6117 | 0.8235 |
|
| | 0.3752 | 14.0 | 105 | 0.6014 | 0.8235 |
|
| | 0.3269 | 14.93 | 112 | 0.6102 | 0.8039 |
|
| | 0.2733 | 16.0 | 120 | 0.6404 | 0.8039 |
|
| | 0.2733 | 16.93 | 127 | 0.5687 | 0.8431 |
|
| | 0.2711 | 18.0 | 135 | 0.6120 | 0.8235 |
|
| | 0.2519 | 18.93 | 142 | 0.6250 | 0.8431 |
|
| | 0.2484 | 20.0 | 150 | 0.6086 | 0.7843 |
|
| | 0.2484 | 20.93 | 157 | 0.6229 | 0.8235 |
|
| | 0.2258 | 22.0 | 165 | 0.6390 | 0.7843 |
|
| | 0.2258 | 22.4 | 168 | 0.6337 | 0.8039 |
|
|
|
|
|
| ### Framework versions
|
|
|
| - Transformers 4.36.2
|
| - Pytorch 2.1.2+cu118
|
| - Datasets 2.16.1
|
| - Tokenizers 0.15.0
|
|
|
