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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: videomae-tiny-binary-finetuned-xd-violence
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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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# videomae-tiny-binary-finetuned-xd-violence
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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: 0.6057
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- Accuracy: 0.6815
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- F1: 0.5197
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- Precision: 0.5965
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- Recall: 0.4604
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- Specificity: 0.8137
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- True Positives: 6205
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- True Negatives: 18337
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- False Positives: 4197
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- False Negatives: 7272
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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: 0.0005
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- train_batch_size: 8
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- eval_batch_size: 8
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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_ratio: 0.1
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- training_steps: 1684
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Specificity | True Positives | True Negatives | False Positives | False Negatives |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-----------:|:--------------:|:--------------:|:---------------:|:---------------:|
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| 0.698 | 0.2506 | 422 | 0.6440 | 0.6324 | 0.3758 | 0.5154 | 0.2957 | 0.8337 | 3985 | 18787 | 3747 | 9492 |
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| 0.6132 | 1.2506 | 844 | 0.6481 | 0.6394 | 0.5759 | 0.5144 | 0.6540 | 0.6307 | 8814 | 14213 | 8321 | 4663 |
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| 0.6364 | 2.2506 | 1266 | 0.6168 | 0.6617 | 0.5356 | 0.5508 | 0.5212 | 0.7458 | 7024 | 16805 | 5729 | 6453 |
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| 0.5219 | 3.2482 | 1684 | 0.6057 | 0.6815 | 0.5197 | 0.5965 | 0.4604 | 0.8137 | 6205 | 18337 | 4197 | 7272 |
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### Framework versions
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- Transformers 4.51.3
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- Pytorch 2.1.0+cu118
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- Datasets 3.6.0
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- Tokenizers 0.21.1
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