| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: microsoft/resnet-18 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: vit-finetuned2 |
| 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. --> |
|
|
| # vit-finetuned2 |
|
|
| This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8828 |
| - Accuracy: 0.746 |
|
|
| ## 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: 0.0002 |
| - train_batch_size: 64 |
| - eval_batch_size: 128 |
| - 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: linear |
| - num_epochs: 20 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 211 | 3.2058 | 0.2 | |
| | No log | 2.0 | 422 | 2.7863 | 0.27 | |
| | 3.5109 | 3.0 | 633 | 2.6225 | 0.306 | |
| | 3.5109 | 4.0 | 844 | 2.3383 | 0.392 | |
| | 2.6956 | 5.0 | 1055 | 2.1045 | 0.456 | |
| | 2.6956 | 6.0 | 1266 | 1.8551 | 0.504 | |
| | 2.6956 | 7.0 | 1477 | 1.6949 | 0.54 | |
| | 2.213 | 8.0 | 1688 | 1.5866 | 0.576 | |
| | 2.213 | 9.0 | 1899 | 1.3373 | 0.646 | |
| | 1.8406 | 10.0 | 2110 | 1.2958 | 0.64 | |
| | 1.8406 | 11.0 | 2321 | 1.3066 | 0.652 | |
| | 1.5618 | 12.0 | 2532 | 1.1972 | 0.664 | |
| | 1.5618 | 13.0 | 2743 | 1.1654 | 0.67 | |
| | 1.5618 | 14.0 | 2954 | 1.0900 | 0.7 | |
| | 1.3308 | 15.0 | 3165 | 1.0244 | 0.704 | |
| | 1.3308 | 16.0 | 3376 | 1.0534 | 0.706 | |
| | 1.1426 | 17.0 | 3587 | 0.9758 | 0.732 | |
| | 1.1426 | 18.0 | 3798 | 0.9583 | 0.716 | |
| | 1.0085 | 19.0 | 4009 | 0.9191 | 0.732 | |
| | 1.0085 | 20.0 | 4220 | 0.8828 | 0.746 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.51.3 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.1 |
|
|
