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Unlearn Cl Ucf101 Videomae Large Salun 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: 0.3518 Accuracy: 0.9169 Test Accuracy: 0.9169 Df Accuracy: 0.9450...

Fontehuggingface.co/jialicheng/unlearn-cl_ucf101_videomae-large_salun_8_42/tree/c1e788065a97304a3367c7cb2b9a22a642fa5861
TipoModeloModelo baseMCG-NJU/videomae-largeVersãoRevision c1e7880Bnota

Fonte do modelo

Tipo
Modelo
Tamanho do arquivo
1,13–2,26 GB
Modelo base
MCG-NJU/videomae-large
Versão
vRevision c1e7880
Atualizado
30 de out. de 2026
Downloads
7
Fonte
Hugging Face

Descrição da fonte

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: 0.3518
  • Accuracy: 0.9169
  • Test Accuracy: 0.9169
  • Df Accuracy: 0.9450
  • Unlearn Overall Accuracy: 0.4860
  • Unlearn Time: 14889.1626

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: 3

Training results

Training LossEpochStepValidation LossAccuracyOverall AccuracyUnlearn Overall AccuracyTime
No log1.02980.40890.98210.46320.4632-1
No log2.05960.35990.95330.48210.4821-1
No log3.08940.35200.94500.48600.4860-1

Framework versions

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

Fontes

1 fonte
Hugging FacePrimárioVersão c1e788065a97304a3367c7cb2b9a22a642fa5861
huggingface.co/jialicheng/unlearn-cl_ucf101_videomae-large_salun_8_42/tree/c1e788065a97304a3367c7cb2b9a22a642fa5861

Verificado 30 de out.

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Repository files

File inventory only; completeness is unverified.

Artefatos de modelo

2 artefatos

model.safetensors

safetensors · FP32 (tensor header) · 1,13 GB · SHA-256 223a8913cc6a…7d98 · Hugging Face

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sal_mask_with_0.5.pt

pt · 2,26 GB · SHA-256 74cdc1c8c640…cb9a · Hugging Face

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Trechos de fonte

3 trechos
Readme14 de ago.huggingface.co/jialicheng/unlearn-cl_ucf101_videomae-large_salun_8_42

--- 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: 0.3518 - Accuracy: 0.9169 - Test Accuracy: 0.9169 - Df Accuracy: 0.9450 - Unlearn Overall Accuracy: 0.4860 - Unlearn Time: 14889.1626 ## 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: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time | |:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|:------------------------:|:----:| | No log | 1.0 | 298 | 0.4089 | 0.9821 | 0.4632 | 0.4632 | -1 | | No log | 2.0 | 596 | 0.3599 | 0.9533 | 0.4821 | 0.4821 | -1 | | No log | 3.0 | 894 | 0.3520 | 0.9450 | 0.4860 | 0.4860 | -1 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.2+cu118 - Datasets 2.18.0 - Tokenizers 0.15.2

Note30 de out.huggingface.co/jialicheng/unlearn-cl_ucf101_videomae-large_salun_8_42

Source context: 7 downloads · 0 likes · Pipeline video-classification · Repo jialicheng/unlearn-cl_ucf101_videomae-large_salun_8_42

Note14 de ago.huggingface.co/jialicheng/unlearn-cl_ucf101_videomae-large_salun_8_42

Source context: 4 downloads · 0 likes · Pipeline video-classification · Repo jialicheng/unlearn-cl_ucf101_videomae-large_salun_8_42