--- license: apache-2.0 base_model: microsoft/beit-base-patch16-224 tags: - generated_from_trainer metrics: - accuracy - precision - recall model-index: - name: beit-base-patch16-224 results: [] --- # beit-base-patch16-224 This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.8528 - Accuracy: 0.8268 - Precision: 0.8303 - Recall: 0.8268 - F1 Score: 0.8283 ## 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: 48 - eval_batch_size: 48 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 192 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 45 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:| | No log | 0.8 | 2 | 0.6993 | 0.5882 | 0.5390 | 0.5882 | 0.5541 | | No log | 2.0 | 5 | 0.5971 | 0.6863 | 0.6806 | 0.6863 | 0.6033 | | No log | 2.8 | 7 | 0.5306 | 0.8039 | 0.8000 | 0.8039 | 0.8006 | | No log | 4.0 | 10 | 0.4828 | 0.7255 | 0.7229 | 0.7255 | 0.6859 | | No log | 4.8 | 12 | 0.3812 | 0.7843 | 0.7786 | 0.7843 | 0.7784 | | 0.5413 | 6.0 | 15 | 0.5268 | 0.7451 | 0.7461 | 0.7451 | 0.7141 | | 0.5413 | 6.8 | 17 | 0.5349 | 0.7451 | 0.8556 | 0.7451 | 0.7502 | | 0.5413 | 8.0 | 20 | 0.4120 | 0.8039 | 0.8485 | 0.8039 | 0.7756 | | 0.5413 | 8.8 | 22 | 0.3156 | 0.8039 | 0.8003 | 0.8039 | 0.7963 | | 0.5413 | 10.0 | 25 | 0.3217 | 0.8039 | 0.8061 | 0.8039 | 0.7909 | | 0.5413 | 10.8 | 27 | 0.5161 | 0.7843 | 0.7870 | 0.7843 | 0.7664 | | 0.0919 | 12.0 | 30 | 0.3677 | 0.8431 | 0.8498 | 0.8431 | 0.8451 | | 0.0919 | 12.8 | 32 | 0.4631 | 0.8431 | 0.8407 | 0.8431 | 0.8405 | | 0.0919 | 14.0 | 35 | 0.5001 | 0.8235 | 0.8214 | 0.8235 | 0.8221 | | 0.0919 | 14.8 | 37 | 0.4489 | 0.8431 | 0.8431 | 0.8431 | 0.8431 | | 0.0919 | 16.0 | 40 | 0.5892 | 0.7843 | 0.7799 | 0.7843 | 0.7731 | | 0.0919 | 16.8 | 42 | 0.6579 | 0.7843 | 0.7799 | 0.7843 | 0.7731 | | 0.006 | 18.0 | 45 | 0.7038 | 0.7843 | 0.7799 | 0.7843 | 0.7731 | | 0.006 | 18.8 | 47 | 0.5864 | 0.8627 | 0.8737 | 0.8627 | 0.8651 | | 0.006 | 20.0 | 50 | 0.5488 | 0.8627 | 0.8737 | 0.8627 | 0.8651 | | 0.006 | 20.8 | 52 | 0.6651 | 0.8039 | 0.8003 | 0.8039 | 0.7963 | | 0.006 | 22.0 | 55 | 0.6265 | 0.8039 | 0.8000 | 0.8039 | 0.8006 | | 0.006 | 22.8 | 57 | 0.5229 | 0.8627 | 0.8653 | 0.8627 | 0.8637 | | 0.0048 | 24.0 | 60 | 0.5421 | 0.8627 | 0.8653 | 0.8627 | 0.8637 | | 0.0048 | 24.8 | 62 | 0.6335 | 0.8235 | 0.8205 | 0.8235 | 0.8187 | | 0.0048 | 26.0 | 65 | 1.0379 | 0.8039 | 0.8201 | 0.8039 | 0.7841 | | 0.0048 | 26.8 | 67 | 0.9758 | 0.8235 | 0.8366 | 0.8235 | 0.8089 | | 0.0048 | 28.0 | 70 | 0.6117 | 0.8235 | 0.8205 | 0.8235 | 0.8187 | | 0.0048 | 28.8 | 72 | 0.5403 | 0.8627 | 0.8613 | 0.8627 | 0.8617 | | 0.0063 | 30.0 | 75 | 0.6469 | 0.8431 | 0.8407 | 0.8431 | 0.8405 | | 0.0063 | 30.8 | 77 | 0.7014 | 0.8235 | 0.8205 | 0.8235 | 0.8187 | | 0.0063 | 32.0 | 80 | 0.7514 | 0.8235 | 0.8205 | 0.8235 | 0.8187 | | 0.0063 | 32.8 | 82 | 0.7771 | 0.8235 | 0.8248 | 0.8235 | 0.8144 | | 0.0063 | 34.0 | 85 | 0.7599 | 0.8039 | 0.8003 | 0.8039 | 0.7963 | | 0.0063 | 34.8 | 87 | 0.7554 | 0.8039 | 0.8003 | 0.8039 | 0.7963 | | 0.0045 | 36.0 | 90 | 0.7308 | 0.8039 | 0.8003 | 0.8039 | 0.7963 | ### Framework versions - Transformers 4.40.1 - Pytorch 2.2.1+cu121 - Datasets 2.19.0 - Tokenizers 0.19.1