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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-large-patch32-384 |
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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: image_classification |
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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: 0.3 |
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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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# image_classification |
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This model is a fine-tuned version of [google/vit-large-patch32-384](https://huggingface.co/google/vit-large-patch32-384) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8452 |
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- Accuracy: 0.3 |
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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: 3e-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: 2 |
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- total_train_batch_size: 32 |
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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_steps: 500 |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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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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| 2.1828 | 1.0 | 20 | 2.1899 | 0.1125 | |
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| 2.1419 | 2.0 | 40 | 2.1018 | 0.1625 | |
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| 2.078 | 3.0 | 60 | 2.1286 | 0.1625 | |
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| 2.0943 | 4.0 | 80 | 2.1462 | 0.15 | |
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| 2.0486 | 5.0 | 100 | 2.0665 | 0.2 | |
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| 1.9442 | 6.0 | 120 | 1.9868 | 0.2562 | |
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| 1.9307 | 7.0 | 140 | 1.9403 | 0.2375 | |
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| 1.8743 | 8.0 | 160 | 1.8866 | 0.275 | |
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| 1.7348 | 9.0 | 180 | 1.7927 | 0.3312 | |
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| 1.6455 | 10.0 | 200 | 1.7579 | 0.3187 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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