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--- |
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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: vit-pretraining-2024_03_25-classifier |
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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: 0.7648975791433892 |
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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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# vit-pretraining-2024_03_25-classifier |
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This model was trained from scratch on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5083 |
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- Accuracy: 0.7649 |
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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: 0.2 |
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- num_epochs: 20 |
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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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| 0.6422 | 1.0 | 537 | 0.6409 | 0.6560 | |
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| 0.5509 | 2.0 | 1074 | 0.5966 | 0.6862 | |
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| 0.5123 | 3.0 | 1611 | 0.5743 | 0.7044 | |
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| 0.5237 | 4.0 | 2148 | 0.5523 | 0.7188 | |
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| 0.5589 | 5.0 | 2685 | 0.5352 | 0.7370 | |
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| 0.5671 | 6.0 | 3222 | 0.5317 | 0.7407 | |
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| 0.5247 | 7.0 | 3759 | 0.5228 | 0.7486 | |
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| 0.4855 | 8.0 | 4296 | 0.5422 | 0.7374 | |
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| 0.5122 | 9.0 | 4833 | 0.5195 | 0.7477 | |
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| 0.5381 | 10.0 | 5370 | 0.5277 | 0.7398 | |
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| 0.5465 | 11.0 | 5907 | 0.5213 | 0.7514 | |
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| 0.4552 | 12.0 | 6444 | 0.5300 | 0.7495 | |
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| 0.5188 | 13.0 | 6981 | 0.5107 | 0.7505 | |
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| 0.5056 | 14.0 | 7518 | 0.5075 | 0.7579 | |
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| 0.4759 | 15.0 | 8055 | 0.5077 | 0.7644 | |
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| 0.6042 | 16.0 | 8592 | 0.5143 | 0.7602 | |
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| 0.4002 | 17.0 | 9129 | 0.5184 | 0.7612 | |
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| 0.4664 | 18.0 | 9666 | 0.5072 | 0.7630 | |
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| 0.4653 | 19.0 | 10203 | 0.5103 | 0.7626 | |
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| 0.4096 | 20.0 | 10740 | 0.5083 | 0.7649 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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