| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: microsoft/resnet-50 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: resnet50 |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: validation |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9926 |
| --- |
| |
| <!-- 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. --> |
|
|
| # resnet50 |
|
|
| This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0210 |
| - Accuracy: 0.9926 |
| - F1 Weighted: 0.9926 |
| - F1 Macro: 0.9925 |
| - Precision Weighted: 0.9926 |
|
|
| ## 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: 128 |
| - eval_batch_size: 256 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 256 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 0.1 |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Weighted | F1 Macro | Precision Weighted | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:------------------:| |
| | 3.7125 | 1.0 | 193 | 0.1263 | 0.961 | 0.9604 | 0.9602 | 0.9628 | |
| | 0.1261 | 2.0 | 386 | 0.0376 | 0.9882 | 0.9882 | 0.9881 | 0.9885 | |
| | 0.0347 | 3.0 | 579 | 0.0232 | 0.9926 | 0.9926 | 0.9925 | 0.9927 | |
| | 0.0165 | 4.0 | 772 | 0.0238 | 0.992 | 0.992 | 0.9919 | 0.9921 | |
| | 0.0109 | 5.0 | 965 | 0.0210 | 0.9926 | 0.9926 | 0.9925 | 0.9926 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
