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Unlearn Cl Ucf101 Videomae Base Neggrad 10 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: -37.0018 Accuracy: 0.0043 Test Accuracy: 0.0043 Df Accuracy: 0.0042...

TipoOtherModelo baseMCG-NJU/videomae-baseVersiónRevision 10bac47Ccalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
329 MB
Modelo base
MCG-NJU/videomae-base
Versión
vRevision 10bac47
Actualizado
3 oct 2026
Descargas
2
Fuente
Hugging Face

Descripción de la fuente

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: -37.0018
  • Accuracy: 0.0043
  • Test Accuracy: 0.0043
  • Df Accuracy: 0.0042
  • Unlearn Overall Accuracy: 0.5000
  • Unlearn Time: 1868.4382

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: 8
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 4
  • 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 log1.0132-37.15940.00420.50000.5000-1
No log2.0164-39.03460.00420.50000.5000-1
No log2.9193-39.50880.00420.50000.5000-1

Framework versions

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

Fuentes

1 fuente
Hugging FacePrincipalVersión 10bac477b4bd8d130945c4b09fcca65ef5f9dfda
huggingface.co/jialicheng/unlearn-cl_ucf101_videomae-base_neggrad_10_42/tree/10bac477b4bd8d130945c4b09fcca65ef5f9dfda

Verificado 21 ago

Artefactos del modelo

1 artefacto

model.safetensors

safetensors · 329 MB · SHA-256 a4ae32c3c324…6463 · Hugging Face

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Extractos de fuentes

2 extractos

--- 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: -37.0018 - Accuracy: 0.0043 - Test Accuracy: 0.0043 - Df Accuracy: 0.0042 - Unlearn Overall Accuracy: 0.5000 - Unlearn Time: 1868.4382 ## 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: 8 - eval_batch_size: 64 - seed: 42 - gradient_accumulation_steps: 4 - 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 | 1.01 | 32 | -37.1594 | 0.0042 | 0.5000 | 0.5000 | -1 | | No log | 2.01 | 64 | -39.0346 | 0.0042 | 0.5000 | 0.5000 | -1 | | No log | 2.91 | 93 | -39.5088 | 0.0042 | 0.5000 | 0.5000 | -1 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.2+cu118 - Datasets 2.18.0 - Tokenizers 0.15.2

Source context: 2 downloads · 0 likes · Pipeline video-classification · Repo jialicheng/unlearn-cl_ucf101_videomae-base_neggrad_10_42