| | --- |
| | license: apache-2.0 |
| | base_model: google/vit-base-patch16-224 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: my_classification |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # my_classification |
| | |
| | This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.3033 |
| | - Accuracy: 0.7277 |
| | |
| | ## 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: 2e-05 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 5.7973 | 1.0 | 175 | 4.2373 | 0.1537 | |
| | | 3.3114 | 2.0 | 350 | 2.8087 | 0.4224 | |
| | | 1.68 | 3.0 | 525 | 1.9823 | 0.5983 | |
| | | 0.7776 | 4.0 | 700 | 1.6113 | 0.6648 | |
| | | 0.3974 | 5.0 | 875 | 1.4166 | 0.6962 | |
| | | 0.1666 | 6.0 | 1050 | 1.3312 | 0.7119 | |
| | | 0.0657 | 7.0 | 1225 | 1.3033 | 0.7277 | |
| | | 0.0315 | 8.0 | 1400 | 1.3021 | 0.7191 | |
| | | 0.0187 | 9.0 | 1575 | 1.2946 | 0.7198 | |
| | | 0.0146 | 10.0 | 1750 | 1.3018 | 0.7191 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.33.3 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.13.3 |
| | |
