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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- fl_image_category_ds |
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metrics: |
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- accuracy |
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model-index: |
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- name: fl_image_category |
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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: fl_image_category_ds |
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type: fl_image_category_ds |
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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: 0.6216216216216216 |
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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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# fl_image_category |
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This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co./microsoft/resnet-18) on the fl_image_category_ds dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9667 |
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- Accuracy: 0.6216 |
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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-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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 5 |
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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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| 1.274 | 1.0 | 88 | 1.2030 | 0.4986 | |
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| 1.069 | 2.0 | 176 | 1.0716 | 0.5605 | |
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| 1.0592 | 3.0 | 264 | 1.0385 | 0.5676 | |
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| 0.9571 | 4.0 | 352 | 0.9746 | 0.6131 | |
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| 0.8975 | 5.0 | 440 | 0.9667 | 0.6216 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.1 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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