| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - cifar10 |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: cifar |
| | results: |
| | - task: |
| | name: Image Classification |
| | type: image-classification |
| | dataset: |
| | name: cifar10 |
| | type: cifar10 |
| | config: plain_text |
| | split: train[:5000] |
| | args: plain_text |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.883 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # cifar |
| |
|
| | 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 cifar10 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4714 |
| | - Accuracy: 0.883 |
| |
|
| | ## 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: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 64 |
| | - 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 1.7956 | 0.99 | 62 | 1.6395 | 0.817 | |
| | | 0.8981 | 2.0 | 125 | 0.8510 | 0.858 | |
| | | 0.6049 | 2.99 | 187 | 0.6666 | 0.878 | |
| | | 0.5427 | 4.0 | 250 | 0.5796 | 0.88 | |
| | | 0.4318 | 4.99 | 312 | 0.5110 | 0.889 | |
| | | 0.3952 | 6.0 | 375 | 0.4339 | 0.907 | |
| | | 0.3544 | 6.99 | 437 | 0.4432 | 0.902 | |
| | | 0.3612 | 8.0 | 500 | 0.4213 | 0.898 | |
| | | 0.3522 | 8.99 | 562 | 0.4474 | 0.884 | |
| | | 0.3096 | 9.92 | 620 | 0.4714 | 0.883 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.28.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.12.0 |
| | - Tokenizers 0.13.3 |
| |
|
