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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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metrics: |
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- accuracy |
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model-index: |
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- name: test_model_8 |
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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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# test_model_8 |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8797 |
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- F1 Macro: 0.0598 |
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- F1 Micro: 0.2121 |
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- F1 Weighted: 0.0845 |
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- Precision Macro: 0.1723 |
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- Precision Micro: 0.2121 |
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- Precision Weighted: 0.2316 |
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- Recall Macro: 0.1486 |
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- Recall Micro: 0.2121 |
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- Recall Weighted: 0.2121 |
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- Accuracy: 0.2121 |
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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: 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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | F1 Weighted | Precision Macro | Precision Micro | Precision Weighted | Recall Macro | Recall Micro | Recall Weighted | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:---------------:|:------------------:|:------------:|:------------:|:---------------:|:--------:| |
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| 1.9439 | 0.8 | 3 | 1.9065 | 0.0541 | 0.1894 | 0.0764 | 0.0625 | 0.1894 | 0.0857 | 0.1327 | 0.1894 | 0.1894 | 0.1894 | |
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| 1.9049 | 1.8 | 6 | 1.8820 | 0.0578 | 0.2045 | 0.0818 | 0.0501 | 0.2045 | 0.0696 | 0.1433 | 0.2045 | 0.2045 | 0.2045 | |
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| 2.3436 | 2.8 | 9 | 1.8773 | 0.0738 | 0.1894 | 0.1022 | 0.0567 | 0.1894 | 0.0780 | 0.1348 | 0.1894 | 0.1894 | 0.1894 | |
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### Framework versions |
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- Transformers 4.48.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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