--- library_name: transformers license: apache-2.0 base_model: google/vit-base-patch16-224 tags: - generated_from_trainer metrics: - accuracy model-index: - name: 21BAI1229 results: [] --- # 21BAI1229 This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.4078 - Accuracy: 0.8734 ## 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: 64 - eval_batch_size: 64 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 256 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 2.6034 | 0.9873 | 39 | 2.0544 | 0.4520 | | 1.4429 | 2.0 | 79 | 0.7736 | 0.7849 | | 0.8307 | 2.9873 | 118 | 0.5456 | 0.8413 | | 0.6814 | 4.0 | 158 | 0.4881 | 0.8516 | | 0.6199 | 4.9873 | 197 | 0.4614 | 0.8528 | | 0.5578 | 6.0 | 237 | 0.4419 | 0.8615 | | 0.5198 | 6.9873 | 276 | 0.4485 | 0.8603 | | 0.4811 | 8.0 | 316 | 0.4355 | 0.8659 | | 0.4568 | 8.9873 | 355 | 0.4182 | 0.8651 | | 0.4268 | 10.0 | 395 | 0.4094 | 0.8702 | | 0.4281 | 10.9873 | 434 | 0.4158 | 0.8706 | | 0.4143 | 12.0 | 474 | 0.4078 | 0.8734 | | 0.4009 | 12.9873 | 513 | 0.4066 | 0.8714 | | 0.3642 | 14.0 | 553 | 0.4131 | 0.8683 | | 0.3659 | 14.9873 | 592 | 0.4047 | 0.8726 | | 0.3487 | 16.0 | 632 | 0.4054 | 0.8710 | | 0.35 | 16.9873 | 671 | 0.4107 | 0.8722 | | 0.3291 | 18.0 | 711 | 0.4099 | 0.8698 | | 0.338 | 18.9873 | 750 | 0.4063 | 0.8718 | | 0.3419 | 19.7468 | 780 | 0.4066 | 0.8702 | ### Framework versions - Transformers 4.46.2 - Pytorch 2.5.0+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3