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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 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: best-model |
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results: [] |
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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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# best-model |
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5533 |
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- Accuracy: 0.8289 |
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- Precision: 0.8457 |
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- Recall: 0.8289 |
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- F1: 0.8320 |
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- Precision Indoor: 0.6897 |
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- Recall Indoor: 0.8696 |
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- F1 Indoor: 0.7692 |
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- Support Indoor: 23 |
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- Precision Notapplicable: 0.8182 |
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- Recall Notapplicable: 0.6923 |
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- F1 Notapplicable: 0.75 |
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- Support Notapplicable: 13 |
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- Precision Outdoor: 0.9444 |
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- Recall Outdoor: 0.85 |
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- F1 Outdoor: 0.8947 |
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- Support Outdoor: 40 |
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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: 0.01 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.05 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Precision Indoor | Recall Indoor | F1 Indoor | Support Indoor | Precision Notapplicable | Recall Notapplicable | F1 Notapplicable | Support Notapplicable | Precision Outdoor | Recall Outdoor | F1 Outdoor | Support Outdoor | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:----------------:|:-------------:|:---------:|:--------------:|:-----------------------:|:--------------------:|:----------------:|:---------------------:|:-----------------:|:--------------:|:----------:|:---------------:| |
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| No log | 1.0 | 19 | 0.9758 | 0.7237 | 0.8166 | 0.7237 | 0.7386 | 0.7059 | 0.5217 | 0.6 | 23 | 0.4483 | 1.0 | 0.6190 | 13 | 1.0 | 0.75 | 0.8571 | 40 | |
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| 0.9607 | 2.0 | 38 | 0.5533 | 0.8289 | 0.8457 | 0.8289 | 0.8320 | 0.6897 | 0.8696 | 0.7692 | 23 | 0.8182 | 0.6923 | 0.75 | 13 | 0.9444 | 0.85 | 0.8947 | 40 | |
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### Framework versions |
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- Transformers 4.57.6 |
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- Pytorch 2.9.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.2 |
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