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Unlearn Cl Ucf101 Videomae Large Bad Teaching 6 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: 0.4961 Accuracy: 0.9047 Test Accuracy: 0.9047 Df Accuracy: 0.9717...

TypeOtherModèle de baseMCG-NJU/videomae-largeVersionRevision a4e0eccBClasse

Source du modèle

Type
Other
Taille du fichier
1,13 GB
Modèle de base
MCG-NJU/videomae-large
Version
vRevision a4e0ecc
Mis à jour
3 oct. 2026
Téléchargements
3
Source
Hugging Face

Description de la source

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: 0.4961
  • Accuracy: 0.9047
  • Test Accuracy: 0.9047
  • Df Accuracy: 0.9717
  • Unlearn Overall Accuracy: 0.4665
  • Unlearn Time: 5297.4909

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: 2
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 8
  • 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 log1.0380.49610.97170.46650.4665-1
No log2.0760.52790.97000.46550.4655-1
No log2.921110.56230.96830.46460.4646-1

Framework versions

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

Sources

1 source
Hugging FacePrincipalVersion a4e0ecc6513ce44bce4c14a819cdd5e86025ac6e
huggingface.co/jialicheng/unlearn-cl_ucf101_videomae-large_bad_teaching_6_42/tree/a4e0ecc6513ce44bce4c14a819cdd5e86025ac6e

Vérifié 21 août

Artefacts du modèle

1 artefact

model.safetensors

safetensors · 1,13 GB · SHA-256 9cc86e27a897…1bc6 · Hugging Face

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Extraits de sources

2 extraits

--- 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: 0.4961 - Accuracy: 0.9047 - Test Accuracy: 0.9047 - Df Accuracy: 0.9717 - Unlearn Overall Accuracy: 0.4665 - Unlearn Time: 5297.4909 ## 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: 2 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 8 - 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 | 1.0 | 38 | 0.4961 | 0.9717 | 0.4665 | 0.4665 | -1 | | No log | 2.0 | 76 | 0.5279 | 0.9700 | 0.4655 | 0.4655 | -1 | | No log | 2.92 | 111 | 0.5623 | 0.9683 | 0.4646 | 0.4646 | -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-large_bad_teaching_6_42