| | --- |
| | license: apache-2.0 |
| | base_model: google/vit-base-patch16-224-in21K |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: Main_Fashion |
| | 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. --> |
| |
|
| | # Main_Fashion |
| | |
| | This model is a fine-tuned version of [google/vit-base-patch16-224-in21K](https://huggingface.co/google/vit-base-patch16-224-in21K) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7633 |
| | - Accuracy: 0.6961 |
| | |
| | ## 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: 16 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 7 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 0.934 | 0.9259 | 100 | 0.9492 | 0.7030 | |
| | | 0.9191 | 1.8519 | 200 | 0.7838 | 0.7401 | |
| | | 0.7774 | 2.7778 | 300 | 0.8152 | 0.7123 | |
| | | 0.5743 | 3.7037 | 400 | 0.7249 | 0.7100 | |
| | | 0.5145 | 4.6296 | 500 | 0.7721 | 0.7077 | |
| | | 0.4713 | 5.5556 | 600 | 0.7182 | 0.7146 | |
| | | 0.4397 | 6.4815 | 700 | 0.7633 | 0.6961 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.40.1 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.19.0 |
| | - Tokenizers 0.19.1 |
| | |
