--- library_name: transformers license: apache-2.0 base_model: facebook/dino-vitb8 tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: dino-vitb8-finetuned-stroke-binary results: [] datasets: - BTX24/tekno21-brain-stroke-dataset-binary pipeline_tag: image-classification --- # dino-vitb8-finetuned-stroke-binary This model is a fine-tuned version of [facebook/dino-vitb8](https://huggingface.co/facebook/dino-vitb8) on an - BTX24/tekno21-brain-stroke-dataset-binary dataset. It achieves the following results on the evaluation set: - Loss: 0.1127 - Accuracy: 0.9597 - F1: 0.9595 - Precision: 0.9602 - Recall: 0.9597 ## 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: 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: 36 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | 0.7965 | 0.6202 | 100 | 0.8312 | 0.5382 | 0.5058 | 0.4968 | 0.5382 | | 0.6839 | 1.2357 | 200 | 0.6796 | 0.6246 | 0.5750 | 0.5991 | 0.6246 | | 0.5662 | 1.8558 | 300 | 0.5344 | 0.7318 | 0.7119 | 0.7377 | 0.7318 | | 0.4408 | 2.4713 | 400 | 0.4082 | 0.8123 | 0.8082 | 0.8120 | 0.8123 | | 0.3611 | 3.0868 | 500 | 0.3335 | 0.8602 | 0.8597 | 0.8596 | 0.8602 | | 0.3121 | 3.7070 | 600 | 0.2746 | 0.8860 | 0.8832 | 0.8914 | 0.8860 | | 0.2614 | 4.3225 | 700 | 0.2299 | 0.9050 | 0.9040 | 0.9058 | 0.9050 | | 0.242 | 4.9426 | 800 | 0.2103 | 0.9177 | 0.9178 | 0.9179 | 0.9177 | | 0.2239 | 5.5581 | 900 | 0.2298 | 0.9082 | 0.9090 | 0.9136 | 0.9082 | | 0.1979 | 6.1736 | 1000 | 0.2059 | 0.9209 | 0.9197 | 0.9230 | 0.9209 | | 0.2082 | 6.7938 | 1100 | 0.1779 | 0.9263 | 0.9261 | 0.9261 | 0.9263 | | 0.1723 | 7.4093 | 1200 | 0.1693 | 0.9308 | 0.9302 | 0.9315 | 0.9308 | | 0.1877 | 8.0248 | 1300 | 0.1681 | 0.9380 | 0.9382 | 0.9385 | 0.9380 | | 0.2 | 8.6450 | 1400 | 0.1482 | 0.9403 | 0.9402 | 0.9402 | 0.9403 | | 0.1642 | 9.2605 | 1500 | 0.1637 | 0.9331 | 0.9322 | 0.9352 | 0.9331 | | 0.1525 | 9.8806 | 1600 | 0.1494 | 0.9421 | 0.9417 | 0.9425 | 0.9421 | | 0.158 | 10.4961 | 1700 | 0.1403 | 0.9484 | 0.9480 | 0.9495 | 0.9484 | | 0.1327 | 11.1116 | 1800 | 0.1329 | 0.9498 | 0.9498 | 0.9498 | 0.9498 | | 0.1465 | 11.7318 | 1900 | 0.1233 | 0.9525 | 0.9524 | 0.9525 | 0.9525 | | 0.1311 | 12.3473 | 2000 | 0.1280 | 0.9521 | 0.9520 | 0.9520 | 0.9521 | | 0.129 | 12.9674 | 2100 | 0.1173 | 0.9557 | 0.9556 | 0.9556 | 0.9557 | | 0.1425 | 13.5829 | 2200 | 0.1190 | 0.9552 | 0.9552 | 0.9552 | 0.9552 | | 0.1256 | 14.1984 | 2300 | 0.1225 | 0.9566 | 0.9563 | 0.9570 | 0.9566 | | 0.1461 | 14.8186 | 2400 | 0.1171 | 0.9588 | 0.9588 | 0.9588 | 0.9588 | | 0.133 | 15.4341 | 2500 | 0.1165 | 0.9548 | 0.9546 | 0.9549 | 0.9548 | | 0.1258 | 16.0496 | 2600 | 0.1302 | 0.9480 | 0.9474 | 0.9500 | 0.9480 | | 0.115 | 16.6698 | 2700 | 0.1320 | 0.9534 | 0.9537 | 0.9552 | 0.9534 | | 0.1134 | 17.2853 | 2800 | 0.1171 | 0.9552 | 0.9549 | 0.9562 | 0.9552 | | 0.1069 | 17.9054 | 2900 | 0.1127 | 0.9597 | 0.9595 | 0.9602 | 0.9597 | ### 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/PbvXd-XrUrNnejf3SYrhI.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/7reTWJDyaIAgh56lHAYgW.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/VGGOMUrfzoDJKiZ3_n4Kl.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/VJQoudhIzRgc_hpaczhgw.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/cdELOOwvLrGRG5MRo2G9Q.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/7WGzzZn2CYK6N10KIStwa.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/LqGssckFyO615Yh81TBsA.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/BEE_9SIRxtVCTLUT6UyNe.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/be8oZaCjODSNz58wZxvl0.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/TZzqT74OT9mqwUZJHkkQq.png)