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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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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: categorAI_img |
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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: 0.8378378378378378 |
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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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# categorAI_img |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7080 |
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- Accuracy: 0.8378 |
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 25 |
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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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| No log | 0.9091 | 5 | 1.8872 | 0.3784 | |
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| 7.7979 | 1.9091 | 10 | 1.7777 | 0.6419 | |
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| 7.7979 | 2.9091 | 15 | 1.6224 | 0.6622 | |
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| 6.9519 | 3.9091 | 20 | 1.4667 | 0.6959 | |
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| 6.9519 | 4.9091 | 25 | 1.3353 | 0.7365 | |
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| 5.7562 | 5.9091 | 30 | 1.2522 | 0.7703 | |
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| 5.7562 | 6.9091 | 35 | 1.1617 | 0.7838 | |
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| 4.7446 | 7.9091 | 40 | 1.0967 | 0.7635 | |
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| 4.7446 | 8.9091 | 45 | 1.0362 | 0.7568 | |
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| 4.0655 | 9.9091 | 50 | 0.9349 | 0.8108 | |
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| 4.0655 | 10.9091 | 55 | 0.9393 | 0.7905 | |
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| 3.5041 | 11.9091 | 60 | 0.8859 | 0.7838 | |
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| 3.5041 | 12.9091 | 65 | 0.9039 | 0.7770 | |
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| 3.0788 | 13.9091 | 70 | 0.8123 | 0.8041 | |
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| 3.0788 | 14.9091 | 75 | 0.7946 | 0.8243 | |
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| 2.7461 | 15.9091 | 80 | 0.8003 | 0.8311 | |
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| 2.7461 | 16.9091 | 85 | 0.8101 | 0.7703 | |
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| 2.4988 | 17.9091 | 90 | 0.7111 | 0.8176 | |
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| 2.4988 | 18.9091 | 95 | 0.7439 | 0.8243 | |
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| 2.3122 | 19.9091 | 100 | 0.7542 | 0.7905 | |
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| 2.3122 | 20.9091 | 105 | 0.7323 | 0.8311 | |
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| 2.3408 | 21.9091 | 110 | 0.7175 | 0.8243 | |
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| 2.3408 | 22.9091 | 115 | 0.7652 | 0.8041 | |
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| 2.2846 | 23.9091 | 120 | 0.7211 | 0.8176 | |
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| 2.2846 | 24.9091 | 125 | 0.7080 | 0.8378 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1.post306 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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