| --- |
| 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-ethos-data |
| 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: 0.7733333333333333 |
| --- |
| |
| <!-- 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-ethos-data |
|
|
| 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: 0.7705 |
| - Accuracy: 0.7733 |
|
|
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 6 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | 1.6788 | 0.9905 | 26 | 1.4249 | 0.4667 | |
| | 1.0638 | 1.9810 | 52 | 1.0795 | 0.64 | |
| | 0.9182 | 2.9714 | 78 | 0.9361 | 0.7133 | |
| | 0.7136 | 4.0 | 105 | 0.8225 | 0.78 | |
| | 0.5723 | 4.9905 | 131 | 0.7854 | 0.76 | |
| | 0.514 | 5.9429 | 156 | 0.7705 | 0.7733 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.40.1 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
|
|
