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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: microsoft/resnet-50 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: trash_classifier3 |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.0018404907975460123 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# trash_classifier3 |
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This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0325 |
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- Accuracy: 0.0018 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.7363 | 1.0 | 102 | 1.9884 | 0.0166 | |
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| 1.5557 | 2.0 | 204 | 2.0147 | 0.0037 | |
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| 1.664 | 3.0 | 306 | 2.0527 | 0.0012 | |
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| 1.3446 | 4.0 | 408 | 2.0362 | 0.0018 | |
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| 1.3102 | 5.0 | 510 | 2.0325 | 0.0018 | |
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### Framework versions |
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- Transformers 4.55.2 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.4 |
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