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--- |
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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: resnet-50 |
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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: 0.9310344827586207 |
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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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# resnet-50 |
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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: 0.6922 |
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- Accuracy: 0.9310 |
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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: 5e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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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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| No log | 0.9655 | 7 | 0.6922 | 0.9310 | |
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| 0.6927 | 1.9310 | 14 | 0.6895 | 0.9310 | |
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| 0.6916 | 2.8966 | 21 | 0.6878 | 0.9310 | |
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| 0.6916 | 4.0 | 29 | 0.6853 | 0.9310 | |
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| 0.6899 | 4.9655 | 36 | 0.6839 | 0.9310 | |
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| 0.6878 | 5.9310 | 43 | 0.6811 | 0.9310 | |
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| 0.6868 | 6.8966 | 50 | 0.6826 | 0.9310 | |
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| 0.6868 | 8.0 | 58 | 0.6804 | 0.9310 | |
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| 0.6864 | 8.9655 | 65 | 0.6801 | 0.9310 | |
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| 0.686 | 9.6552 | 70 | 0.6800 | 0.9310 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.1+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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