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Unlearn Cl Ucf101 Videomae Base Random Label 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: 0.8124 Accuracy: 0.7958 Test Accuracy: 0.7958 Df Accuracy: 0.9353...

TypeOtherModèle de baseMCG-NJU/videomae-baseVersionRevision 4bf17aaCClasse

Source du modèle

Type
Other
Taille du fichier
329 MB
Modèle de base
MCG-NJU/videomae-base
Version
vRevision 4bf17aa
Mis à jour
1 oct. 2026
Téléchargements
2
Source
Hugging Face

Description de la source

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: 0.8124
  • Accuracy: 0.7958
  • Test Accuracy: 0.7958
  • Df Accuracy: 0.9353
  • Unlearn Overall Accuracy: 0.4302
  • Unlearn Time: 4452.2733

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 log1.013000.82410.95380.42160.4216-1
No log2.016001.00170.88920.42490.4249-1
No log2.998940.81210.93530.43020.4302-1

Framework versions

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

Sources

1 source
Hugging FacePrincipalVersion 4bf17aa409f330ec2bab0a8e9287f9cef1288698
huggingface.co/jialicheng/unlearn-cl_ucf101_videomae-base_random_label_10_42/tree/4bf17aa409f330ec2bab0a8e9287f9cef1288698

Vérifié 21 août

Artefacts du modèle

1 artefact

model.safetensors

safetensors · 329 MB · SHA-256 5d35689b0bf1…4434 · Hugging Face

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Extraits de sources

2 extraits

--- 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: 0.8124 - Accuracy: 0.7958 - Test Accuracy: 0.7958 - Df Accuracy: 0.9353 - Unlearn Overall Accuracy: 0.4302 - Unlearn Time: 4452.2733 ## 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 | 300 | 0.8241 | 0.9538 | 0.4216 | 0.4216 | -1 | | No log | 2.01 | 600 | 1.0017 | 0.8892 | 0.4249 | 0.4249 | -1 | | No log | 2.99 | 894 | 0.8121 | 0.9353 | 0.4302 | 0.4302 | -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_random_label_10_42