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Unlearn Ucf101 Videomae Large Scrub 8 42

This model is a fine-tuned version of MCG-NJU/videomae-large on the ucf101 dataset. It achieves the following results on the evaluation set: Loss: 0.3255 Accuracy: 0.9403 Test Accuracy: 0.9403 Df Accuracy: 1.0...

ArtModellBasismodellMCG-NJU/videomae-largeVersionRevision e3e5f6eBBewertung

Modellquelle

Art
Modell
Dateigröße
1,13 GB
Basismodell
MCG-NJU/videomae-large
Version
vRevision e3e5f6e
Aktualisiert
30. Okt. 2026
Downloads
9
Quelle
Hugging Face

Quellenbeschreibung

ucf101_42

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

  • Loss: 0.3255
  • Accuracy: 0.9403
  • Test Accuracy: 0.9403
  • Df Accuracy: 1.0
  • Unlearn Overall Accuracy: 0.4701
  • Unlearn Time: 11529.0707

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: 32
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1.5

Training results

Training LossEpochStepValidation LossAccuracyOverall AccuracyUnlearn Overall AccuracyTime
No log1.02740.31930.99960.46910.4691-1
No log1.494080.32551.00.47010.4701-1

Framework versions

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

Quellen

1 Quelle
Hugging FacePrimärVersion e3e5f6e4952791068178e6631dbef066090b20d7
huggingface.co/jialicheng/unlearn_ucf101_videomae-large_scrub_8_42/tree/e3e5f6e4952791068178e6631dbef066090b20d7

Verifiziert 30. Okt.

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Modellartefakte

1 Artefakt

model.safetensors

safetensors · FP32 (tensor header) · 1,13 GB · SHA-256 9641f5764f0e…72a6 · Hugging Face

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Quellenauszüge

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--- license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-large 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-large](https://huggingface.co/MCG-NJU/videomae-large) on the ucf101 dataset. It achieves the following results on the evaluation set: - Loss: 0.3255 - Accuracy: 0.9403 - Test Accuracy: 0.9403 - Df Accuracy: 1.0 - Unlearn Overall Accuracy: 0.4701 - Unlearn Time: 11529.0707 ## 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: 32 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1.5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time | |:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|:------------------------:|:----:| | No log | 1.0 | 274 | 0.3193 | 0.9996 | 0.4691 | 0.4691 | -1 | | No log | 1.49 | 408 | 0.3255 | 1.0 | 0.4701 | 0.4701 | -1 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.2+cu118 - Datasets 2.18.0 - Tokenizers 0.15.2

Source context: 9 downloads · 0 likes · Pipeline video-classification · Repo jialicheng/unlearn_ucf101_videomae-large_scrub_8_42

Source context: 3 downloads · 0 likes · Pipeline video-classification · Repo jialicheng/unlearn_ucf101_videomae-large_scrub_8_42