| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: microsoft/resnet-50 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: trash_classifier2 |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.029447852760736196 |
| --- |
| |
| <!-- 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. --> |
|
|
| # trash_classifier2 |
| |
| 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: 2.0483 |
| - Accuracy: 0.0294 |
| |
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - 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 |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.8831 | 1.0 | 102 | 2.1049 | 0.0018 | |
| | 0.7466 | 2.0 | 204 | 2.0777 | 0.0117 | |
| | 1.0559 | 3.0 | 306 | 2.1094 | 0.0160 | |
| | 0.4889 | 4.0 | 408 | 2.0512 | 0.0245 | |
| | 0.5925 | 5.0 | 510 | 2.0483 | 0.0294 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.55.2 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.21.4 |
|
|
