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--- |
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license: mit |
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base_model: shi-labs/nat-mini-in1k-224 |
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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: msi_mini |
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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: validation |
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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: 0.6228683254123567 |
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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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# msi_mini |
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This model is a fine-tuned version of [shi-labs/nat-mini-in1k-224](https://huggingface.co/shi-labs/nat-mini-in1k-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5314 |
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- Accuracy: 0.6229 |
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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: 1e-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: 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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| 0.428 | 1.0 | 2015 | 0.8665 | 0.6079 | |
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| 0.3163 | 2.0 | 4031 | 1.0921 | 0.6169 | |
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| 0.2805 | 3.0 | 6047 | 1.1998 | 0.6082 | |
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| 0.2251 | 4.0 | 8063 | 1.2788 | 0.6126 | |
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| 0.1988 | 5.0 | 10078 | 1.3336 | 0.6121 | |
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| 0.1794 | 6.0 | 12094 | 1.3361 | 0.6224 | |
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| 0.1724 | 7.0 | 14110 | 1.5478 | 0.6097 | |
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| 0.1739 | 8.0 | 16126 | 1.6165 | 0.6169 | |
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| 0.1637 | 9.0 | 18141 | 1.5974 | 0.6134 | |
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| 0.1667 | 10.0 | 20150 | 1.5314 | 0.6229 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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