Zum Inhalt springen
ModelAufgelistetExtern
Herunterladen

Unlearn Cl Ucf101 Videomae Base Bad Teaching 6 42

This model is a fine-tuned version of MCG-NJU/videomae-base on the ucf101 dataset. It achieves the following results on the evaluation set: Loss: 0.9477 Accuracy: 0.7900 Test Accuracy: 0.7900 Df Accuracy: 0.9602...

ArtOtherBasismodellMCG-NJU/videomae-baseVersionRevision 8ca6486BBewertung

Modellquelle

Art
Other
Dateigröße
329 MB
Basismodell
MCG-NJU/videomae-base
Version
vRevision 8ca6486
Aktualisiert
4. Okt. 2026
Downloads
3
Quelle
Hugging Face

Quellenbeschreibung

ucf101_42

This model is a fine-tuned version of MCG-NJU/videomae-base on the ucf101 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9477
  • Accuracy: 0.7900
  • Test Accuracy: 0.7900
  • Df Accuracy: 0.9602
  • Unlearn Overall Accuracy: 0.4149
  • Unlearn Time: 1925.8162

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: 5e-05
  • train_batch_size: 4
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training LossEpochStepValidation LossAccuracyOverall AccuracyUnlearn Overall AccuracyTime
No log1.05400.96930.95730.41210.4121-1
No log2.05800.95300.95790.41490.4149-1
No log2.891140.94770.96020.41490.4149-1

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.2+cu118
  • Datasets 2.18.0
  • Tokenizers 0.15.2

Quellen

1 Quelle
Hugging FacePrimärVersion 8ca64869bb3fbcdc2748e9665a65da56b222a587
huggingface.co/jialicheng/unlearn-cl_ucf101_videomae-base_bad_teaching_6_42/tree/8ca64869bb3fbcdc2748e9665a65da56b222a587

Verifiziert 21. Aug.

Modellartefakte

1 Artefakt

model.safetensors

safetensors · 329 MB · SHA-256 b753a97f5b6b…a2f9 · Hugging Face

Download file

Quellenauszüge

2 Auszüge

--- license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base tags: - video-classification - generated_from_trainer metrics: - accuracy model-index: - name: ucf101_42 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. --> # ucf101_42 This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on the ucf101 dataset. It achieves the following results on the evaluation set: - Loss: 0.9477 - Accuracy: 0.7900 - Test Accuracy: 0.7900 - Df Accuracy: 0.9602 - Unlearn Overall Accuracy: 0.4149 - Unlearn Time: 1925.8162 ## 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: 5e-05 - train_batch_size: 4 - eval_batch_size: 64 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time | |:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|:------------------------:|:----:| | No log | 1.05 | 40 | 0.9693 | 0.9573 | 0.4121 | 0.4121 | -1 | | No log | 2.05 | 80 | 0.9530 | 0.9579 | 0.4149 | 0.4149 | -1 | | No log | 2.89 | 114 | 0.9477 | 0.9602 | 0.4149 | 0.4149 | -1 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.2+cu118 - Datasets 2.18.0 - Tokenizers 0.15.2

Source context: 3 downloads · 0 likes · Pipeline video-classification · Repo jialicheng/unlearn-cl_ucf101_videomae-base_bad_teaching_6_42