| | --- |
| | license: apache-2.0 |
| | tags: |
| | - image-classification |
| | - generated_from_trainer |
| | datasets: |
| | - beans |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: vit-base-beans |
| | results: |
| | - task: |
| | name: Image Classification |
| | type: image-classification |
| | dataset: |
| | name: beans |
| | type: beans |
| | config: default |
| | split: validation |
| | args: default |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.9924812030075187 |
| | --- |
| | |
| | <!-- 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-beans |
| |
|
| | 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 beans dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0226 |
| | - Accuracy: 0.9925 |
| |
|
| | ## 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: 0.0002 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 4 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.3365 | 0.38 | 50 | 0.2455 | 0.9323 | |
| | | 0.1728 | 0.77 | 100 | 0.1544 | 0.9549 | |
| | | 0.1519 | 1.15 | 150 | 0.1072 | 0.9624 | |
| | | 0.0209 | 1.54 | 200 | 0.1594 | 0.9624 | |
| | | 0.0206 | 1.92 | 250 | 0.0913 | 0.9699 | |
| | | 0.0135 | 2.31 | 300 | 0.1488 | 0.9624 | |
| | | 0.0079 | 2.69 | 350 | 0.0226 | 0.9925 | |
| | | 0.0074 | 3.08 | 400 | 0.0582 | 0.9925 | |
| | | 0.0064 | 3.46 | 450 | 0.0984 | 0.9774 | |
| | | 0.0061 | 3.85 | 500 | 0.1151 | 0.9699 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.28.1 |
| | - Pytorch 2.0.0+cu117 |
| | - Datasets 2.11.0 |
| | - Tokenizers 0.13.3 |
| |
|
