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--- |
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library_name: transformers |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: profesor_MViT_O_RWF2000 |
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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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# profesor_MViT_O_RWF2000 |
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2973 |
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- Accuracy: 0.9237 |
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- F1: 0.9237 |
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- Precision: 0.9252 |
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- Recall: 0.9237 |
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- Roc Auc: 0.9762 |
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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: 1e-05 |
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- train_batch_size: 20 |
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- eval_batch_size: 20 |
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- seed: 42 |
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- optimizer: Use 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: 225 |
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- training_steps: 2250 |
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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 | F1 | Precision | Recall | Roc Auc | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------:| |
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| 0.4841 | 2.0324 | 225 | 0.3886 | 0.8947 | 0.8947 | 0.8947 | 0.8947 | 0.9512 | |
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| 0.2697 | 5.0311 | 450 | 0.2617 | 0.9158 | 0.9157 | 0.9175 | 0.9158 | 0.9655 | |
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| 0.1796 | 8.0298 | 675 | 0.2392 | 0.9184 | 0.9184 | 0.9190 | 0.9184 | 0.9725 | |
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| 0.1444 | 11.0284 | 900 | 0.2590 | 0.9184 | 0.9184 | 0.9187 | 0.9184 | 0.9755 | |
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| 0.1296 | 14.0271 | 1125 | 0.2587 | 0.9211 | 0.9210 | 0.9218 | 0.9211 | 0.9738 | |
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| 0.0952 | 17.0258 | 1350 | 0.2924 | 0.9211 | 0.9208 | 0.9258 | 0.9211 | 0.9719 | |
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| 0.1148 | 20.0244 | 1575 | 0.2497 | 0.9263 | 0.9263 | 0.9264 | 0.9263 | 0.9777 | |
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| 0.0969 | 23.0231 | 1800 | 0.2806 | 0.9289 | 0.9289 | 0.9304 | 0.9289 | 0.9775 | |
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| 0.0696 | 26.0218 | 2025 | 0.3203 | 0.9263 | 0.9263 | 0.9267 | 0.9263 | 0.9771 | |
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| 0.0915 | 29.0204 | 2250 | 0.3062 | 0.9263 | 0.9263 | 0.9263 | 0.9263 | 0.9740 | |
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### Framework versions |
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- Transformers 4.46.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 3.0.2 |
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- Tokenizers 0.20.1 |
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