| | --- |
| | 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: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # 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 |
| | |
