End of training

README.md

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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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