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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: deit-tiny-patch16-224-finetuned-papsmear |
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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: 0.9117647058823529 |
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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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# deit-tiny-patch16-224-finetuned-papsmear |
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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: 0.3421 |
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- Accuracy: 0.9118 |
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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: 15 |
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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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| 0.3521 | 0.9870 | 19 | 0.4595 | 0.8235 | |
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| 0.335 | 1.9740 | 38 | 0.4491 | 0.8603 | |
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| 0.3248 | 2.9610 | 57 | 0.4196 | 0.875 | |
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| 0.3271 | 4.0 | 77 | 0.5467 | 0.8015 | |
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| 0.3286 | 4.9870 | 96 | 0.4768 | 0.8162 | |
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| 0.2854 | 5.9740 | 115 | 0.4147 | 0.8676 | |
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| 0.2291 | 6.9610 | 134 | 0.4321 | 0.8676 | |
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| 0.2619 | 8.0 | 154 | 0.5726 | 0.8235 | |
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| 0.2196 | 8.9870 | 173 | 0.4344 | 0.8676 | |
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| 0.2116 | 9.9740 | 192 | 0.3809 | 0.875 | |
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| 0.1913 | 10.9610 | 211 | 0.3757 | 0.8603 | |
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| 0.1604 | 12.0 | 231 | 0.3551 | 0.8897 | |
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| 0.1307 | 12.9870 | 250 | 0.3330 | 0.8971 | |
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| 0.1425 | 13.9740 | 269 | 0.3421 | 0.9118 | |
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| 0.141 | 14.8052 | 285 | 0.3409 | 0.9118 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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