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---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: videomae-tiny-binary-finetuned-xd-violence
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# videomae-tiny-binary-finetuned-xd-violence
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6057
- Accuracy: 0.6815
- F1: 0.5197
- Precision: 0.5965
- Recall: 0.4604
- Specificity: 0.8137
- True Positives: 6205
- True Negatives: 18337
- False Positives: 4197
- False Negatives: 7272
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1684
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Specificity | True Positives | True Negatives | False Positives | False Negatives |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-----------:|:--------------:|:--------------:|:---------------:|:---------------:|
| 0.698 | 0.2506 | 422 | 0.6440 | 0.6324 | 0.3758 | 0.5154 | 0.2957 | 0.8337 | 3985 | 18787 | 3747 | 9492 |
| 0.6132 | 1.2506 | 844 | 0.6481 | 0.6394 | 0.5759 | 0.5144 | 0.6540 | 0.6307 | 8814 | 14213 | 8321 | 4663 |
| 0.6364 | 2.2506 | 1266 | 0.6168 | 0.6617 | 0.5356 | 0.5508 | 0.5212 | 0.7458 | 7024 | 16805 | 5729 | 6453 |
| 0.5219 | 3.2482 | 1684 | 0.6057 | 0.6815 | 0.5197 | 0.5965 | 0.4604 | 0.8137 | 6205 | 18337 | 4197 | 7272 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.1.0+cu118
- Datasets 3.6.0
- Tokenizers 0.21.1
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