--- library_name: transformers license: apache-2.0 base_model: microsoft/resnet-18 tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: student results: [] --- # student This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.0839 - Accuracy: 0.4336 - Precision: 0.5017 - Recall: 0.4336 - F1: 0.4223 ## 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: 0.0003 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - 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: 1 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | 4.3903 | 0.012 | 150 | 4.2290 | 0.0146 | 0.0134 | 0.0146 | 0.0083 | | 3.846 | 0.024 | 300 | 3.6356 | 0.0838 | 0.0946 | 0.0838 | 0.0592 | | 3.3778 | 0.036 | 450 | 3.0217 | 0.1558 | 0.2091 | 0.1558 | 0.1167 | | 2.9266 | 0.048 | 600 | 2.6267 | 0.1918 | 0.2768 | 0.1918 | 0.1498 | | 2.7657 | 0.06 | 750 | 2.3280 | 0.2335 | 0.3684 | 0.2335 | 0.1946 | | 2.6257 | 0.072 | 900 | 2.1951 | 0.2758 | 0.3689 | 0.2758 | 0.2381 | | 2.4699 | 0.084 | 1050 | 2.3175 | 0.2424 | 0.3960 | 0.2424 | 0.2101 | | 2.5352 | 0.096 | 1200 | 2.2917 | 0.2533 | 0.3728 | 0.2533 | 0.2284 | | 2.4032 | 0.108 | 1350 | 2.4920 | 0.251 | 0.3818 | 0.251 | 0.2225 | | 2.332 | 0.12 | 1500 | 2.3880 | 0.2639 | 0.3638 | 0.2639 | 0.2324 | | 2.3968 | 0.132 | 1650 | 2.4804 | 0.2687 | 0.3862 | 0.2687 | 0.2531 | | 2.3922 | 0.144 | 1800 | 2.3411 | 0.2886 | 0.4126 | 0.2886 | 0.2600 | | 2.3328 | 0.156 | 1950 | 2.2690 | 0.3191 | 0.3973 | 0.3191 | 0.2896 | | 2.3191 | 0.168 | 2100 | 2.1504 | 0.3387 | 0.4172 | 0.3387 | 0.3161 | | 2.1208 | 0.18 | 2250 | 2.1226 | 0.3369 | 0.4232 | 0.3369 | 0.3154 | | 2.2256 | 0.192 | 2400 | 2.0580 | 0.3629 | 0.4330 | 0.3629 | 0.3372 | | 2.1618 | 0.204 | 2550 | 2.0567 | 0.3585 | 0.4509 | 0.3585 | 0.3360 | | 2.2237 | 0.216 | 2700 | 2.3808 | 0.3446 | 0.4299 | 0.3446 | 0.3254 | | 2.0754 | 0.228 | 2850 | 2.2442 | 0.3718 | 0.4656 | 0.3718 | 0.3529 | | 1.9684 | 0.24 | 3000 | 2.1301 | 0.3848 | 0.4569 | 0.3848 | 0.3590 | | 2.082 | 0.252 | 3150 | 2.0963 | 0.3734 | 0.4557 | 0.3734 | 0.3533 | | 2.0737 | 0.264 | 3300 | 2.2619 | 0.3621 | 0.4506 | 0.3621 | 0.3443 | | 2.0049 | 0.276 | 3450 | 2.3372 | 0.3748 | 0.4527 | 0.3748 | 0.3542 | | 1.9876 | 0.288 | 3600 | 2.0522 | 0.4025 | 0.4759 | 0.4025 | 0.3818 | | 1.9218 | 0.3 | 3750 | 2.1785 | 0.4002 | 0.4704 | 0.4002 | 0.3863 | | 1.9899 | 0.312 | 3900 | 2.3298 | 0.4059 | 0.4758 | 0.4059 | 0.3852 | | 1.9478 | 0.324 | 4050 | 2.0669 | 0.4245 | 0.4732 | 0.4245 | 0.4033 | | 1.9293 | 0.336 | 4200 | 2.1866 | 0.4154 | 0.4885 | 0.4154 | 0.3986 | | 1.8939 | 0.348 | 4350 | 2.1652 | 0.4159 | 0.4788 | 0.4159 | 0.3944 | | 1.8356 | 0.36 | 4500 | 2.1702 | 0.4245 | 0.4706 | 0.4245 | 0.4002 | | 1.8724 | 0.372 | 4650 | 2.1267 | 0.4282 | 0.4825 | 0.4282 | 0.4089 | | 1.7633 | 0.384 | 4800 | 2.1603 | 0.4262 | 0.4896 | 0.4262 | 0.4065 | | 1.8592 | 0.396 | 4950 | 2.0575 | 0.4393 | 0.4837 | 0.4393 | 0.4187 | | 1.7407 | 0.408 | 5100 | 2.0839 | 0.4336 | 0.5017 | 0.4336 | 0.4223 | ### Framework versions - Transformers 4.57.3 - Pytorch 2.9.1+cu128 - Datasets 4.4.2 - Tokenizers 0.22.1