--- library_name: transformers license: apache-2.0 base_model: facebook/deit-base-patch16-224 tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: deit-base-patch16-224-finetuned-stroke-binary results: [] datasets: - BTX24/tekno21-brain-stroke-dataset-binary --- # deit-base-patch16-224-finetuned-stroke-binary This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on an BTX24/tekno21-brain-stroke-dataset-binary dataset. It achieves the following results on the evaluation set: - Loss: 0.1527 - Accuracy: 0.9489 - F1: 0.9484 - Precision: 0.9505 - Recall: 0.9489 ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 48 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | 0.1646 | 0.6202 | 100 | 0.1588 | 0.9430 | 0.9425 | 0.9442 | 0.9430 | | 0.1417 | 1.2357 | 200 | 0.1640 | 0.9439 | 0.9433 | 0.9458 | 0.9439 | | 0.1681 | 1.8558 | 300 | 0.1622 | 0.9453 | 0.9447 | 0.9470 | 0.9453 | | 0.1512 | 2.4713 | 400 | 0.1510 | 0.9435 | 0.9430 | 0.9441 | 0.9435 | | 0.1506 | 3.0868 | 500 | 0.1913 | 0.9340 | 0.9327 | 0.9391 | 0.9340 | | 0.1654 | 3.7070 | 600 | 0.1679 | 0.9426 | 0.9419 | 0.9442 | 0.9426 | | 0.1482 | 4.3225 | 700 | 0.1551 | 0.9403 | 0.9402 | 0.9402 | 0.9403 | | 0.1599 | 4.9426 | 800 | 0.1489 | 0.9462 | 0.9457 | 0.9471 | 0.9462 | | 0.1477 | 5.5581 | 900 | 0.1437 | 0.9426 | 0.9424 | 0.9425 | 0.9426 | | 0.1308 | 6.1736 | 1000 | 0.1527 | 0.9417 | 0.9414 | 0.9416 | 0.9417 | | 0.1362 | 6.7938 | 1100 | 0.1608 | 0.9426 | 0.9421 | 0.9432 | 0.9426 | | 0.1494 | 7.4093 | 1200 | 0.1601 | 0.9435 | 0.9429 | 0.9451 | 0.9435 | | 0.1592 | 8.0248 | 1300 | 0.1430 | 0.9430 | 0.9429 | 0.9429 | 0.9430 | | 0.16 | 8.6450 | 1400 | 0.1504 | 0.9457 | 0.9451 | 0.9475 | 0.9457 | | 0.1245 | 9.2605 | 1500 | 0.1506 | 0.9462 | 0.9458 | 0.9470 | 0.9462 | | 0.1397 | 9.8806 | 1600 | 0.1971 | 0.9313 | 0.9300 | 0.9359 | 0.9313 | | 0.1396 | 10.4961 | 1700 | 0.1527 | 0.9489 | 0.9484 | 0.9505 | 0.9489 | ### Framework versions - Transformers 4.48.3 - Pytorch 2.6.0+cu124 - Datasets 3.4.0 - Tokenizers 0.21.0 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/IFuGQ-kkCjVH--4eyht0R.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/CztgY9KMJ5AhHY2TGo7qk.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/REn-aZtdJ8bAm4_lWSJDV.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/rZhYIlfmQg62Pq-1vt71j.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/75hOug5_xZeyk69eAW8as.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/NAomNblJJoYM1ki1caw1h.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/rOY6uq2Tb2W4pwYygtws3.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/MiiBgBt1SVoGA1DGjCzBR.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/6aYsp0Q01uKGu7nFRF0jK.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/1IlTpcATEDWXVO3ZVU8yc.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/i4g8AM9nePnUTPRPmSBAd.png)