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--- |
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license: apache-2.0 |
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base_model: facebook/deit-tiny-patch16-224 |
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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: hushem_40x_deit_tiny_f2 |
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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: test |
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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: 0.6666666666666666 |
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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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# hushem_40x_deit_tiny_f2 |
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This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co./facebook/deit-tiny-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5181 |
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- Accuracy: 0.6667 |
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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: 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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| 0.1217 | 1.0 | 107 | 1.3584 | 0.6 | |
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| 0.0223 | 2.0 | 214 | 1.3123 | 0.7111 | |
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| 0.0028 | 2.99 | 321 | 1.5329 | 0.6667 | |
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| 0.0063 | 4.0 | 429 | 1.6403 | 0.6889 | |
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| 0.0001 | 5.0 | 536 | 1.5983 | 0.6667 | |
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| 0.0 | 6.0 | 643 | 1.5035 | 0.6667 | |
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| 0.0 | 6.99 | 750 | 1.5067 | 0.6444 | |
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| 0.0 | 8.0 | 858 | 1.5121 | 0.6667 | |
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| 0.0 | 9.0 | 965 | 1.5168 | 0.6667 | |
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| 0.0 | 9.98 | 1070 | 1.5181 | 0.6667 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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