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--- |
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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: vit-base-patch16-224-in21k-mobile-eye-tracking-dataset-v2 |
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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: 0.9898089171974522 |
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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-base-patch16-224-in21k-mobile-eye-tracking-dataset-v2 |
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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: 0.0542 |
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- Accuracy: 0.9898 |
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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: 24 |
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- eval_batch_size: 24 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 96 |
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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 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.024 | 0.99 | 73 | 0.0769 | 0.9809 | |
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| 0.0236 | 1.99 | 147 | 0.1111 | 0.9745 | |
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| 0.0172 | 3.0 | 221 | 0.0542 | 0.9898 | |
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| 0.0114 | 4.0 | 295 | 0.0630 | 0.9885 | |
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| 0.0051 | 4.99 | 368 | 0.0674 | 0.9860 | |
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| 0.0044 | 5.99 | 442 | 0.0640 | 0.9885 | |
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| 0.0037 | 7.0 | 516 | 0.0646 | 0.9885 | |
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| 0.0034 | 8.0 | 590 | 0.0652 | 0.9885 | |
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| 0.0032 | 8.99 | 663 | 0.0656 | 0.9885 | |
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| 0.0032 | 9.9 | 730 | 0.0657 | 0.9885 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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