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--- |
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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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- f1 |
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model-index: |
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- name: vit-large-patch32-384 |
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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: F1 |
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type: f1 |
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value: 0.9763018966303854 |
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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-large-patch32-384 |
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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: 0.0127 |
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- F1: 0.9763 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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 | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.1312 | 0.99 | 53 | 0.1215 | 0.7860 | |
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| 0.0831 | 1.99 | 107 | 0.0570 | 0.9350 | |
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| 0.0441 | 3.0 | 161 | 0.0348 | 0.9475 | |
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| 0.0423 | 4.0 | 215 | 0.0342 | 0.9186 | |
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| 0.0249 | 4.99 | 268 | 0.0232 | 0.9594 | |
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| 0.0168 | 5.99 | 322 | 0.0279 | 0.9414 | |
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| 0.0098 | 7.0 | 376 | 0.0242 | 0.9460 | |
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| 0.0133 | 8.0 | 430 | 0.0181 | 0.9637 | |
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| 0.0156 | 8.99 | 483 | 0.0101 | 0.9804 | |
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| 0.0114 | 9.86 | 530 | 0.0127 | 0.9763 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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