End of training

README.md

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+---
+library_name: transformers
+license: cc-by-nc-4.0
+base_model: MCG-NJU/videomae-base-finetuned-ssv2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: videomae-base-ssv2-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-base-ssv2-binary-finetuned-xd-violence
+
+This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-ssv2](https://huggingface.co/MCG-NJU/videomae-base-finetuned-ssv2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6173
+- Accuracy: 0.6712
+- F1: 0.4986
+- Precision: 0.5807
+- Recall: 0.4368
+- Specificity: 0.8114
+- True Positives: 5887
+- True Negatives: 18284
+- False Positives: 4250
+- False Negatives: 7590
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-----------:|:--------------:|:--------------:|:---------------:|:---------------:|
+| 0.6785        | 0.2506 | 422  | 0.6556          | 0.6638   | 0.4328 | 0.5870    | 0.3427 | 0.8558      | 4619           | 19284          | 3250            | 8858            |
+| 0.6774        | 1.2506 | 844  | 0.6571          | 0.6407   | 0.5602 | 0.5169    | 0.6115 | 0.6582      | 8241           | 14832          | 7702            | 5236            |
+| 0.6654        | 2.2506 | 1266 | 0.6169          | 0.6635   | 0.5385 | 0.5532    | 0.5246 | 0.7466      | 7070           | 16823          | 5711            | 6407            |
+| 0.5013        | 3.2482 | 1684 | 0.6173          | 0.6712   | 0.4986 | 0.5807    | 0.4368 | 0.8114      | 5887           | 18284          | 4250            | 7590            |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.1.0+cu118
+- Datasets 3.6.0
+- Tokenizers 0.21.1

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runs/Jul31_08-47-15_DESKTOP-JCNIME4/events.out.tfevents.1753948041.DESKTOP-JCNIME4.7868.0

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