Unlearn Ucf101 Videomae Large Bad Teaching 10 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: 0.7369 Accuracy: 0.884 Test Accuracy: 0.884 Df Accuracy: 0.9510...
Source du modèle
- Type
- Modèle
- Taille du fichier
- 1,13 GB
- Modèle de base
- MCG-NJU/videomae-large
- Version
- vRevision adc772a
- Mis à jour
- 30 oct. 2026
- Téléchargements
- 8
- 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: 0.7369
- Accuracy: 0.884
- Test Accuracy: 0.884
- Df Accuracy: 0.9510
- Unlearn Overall Accuracy: 0.4665
- Unlearn Time: 6701.2192
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 | 1.01 | 64 | 0.5945 | 0.9612 | 0.4648 | 0.4648 | -1 |
| No log | 2.01 | 128 | 0.6980 | 0.9493 | 0.4659 | 0.4659 | -1 |
| No log | 2.97 | 189 | 0.7369 | 0.9510 | 0.4665 | 0.4665 | -1 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
Sources
1 source
Sources
1 sourceVérifié 30 oct.
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Artefacts du modèle
1 artefact
Artefacts du modèle
1 artefactmodel.safetensors
safetensors · FP32 (tensor header) · 1,13 GB · SHA-256 9c4423d0b465…cbab · Hugging Face
Download fileExtraits de sources
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Extraits de sources
3 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: 0.7369 - Accuracy: 0.884 - Test Accuracy: 0.884 - Df Accuracy: 0.9510 - Unlearn Overall Accuracy: 0.4665 - Unlearn Time: 6701.2192 ## 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 | 1.01 | 64 | 0.5945 | 0.9612 | 0.4648 | 0.4648 | -1 | | No log | 2.01 | 128 | 0.6980 | 0.9493 | 0.4659 | 0.4659 | -1 | | No log | 2.97 | 189 | 0.7369 | 0.9510 | 0.4665 | 0.4665 | -1 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.2+cu118 - Datasets 2.18.0 - Tokenizers 0.15.2
Source context: 8 downloads · 0 likes · Pipeline video-classification · Repo jialicheng/unlearn_ucf101_videomae-large_bad_teaching_10_42
Source context: 4 downloads · 0 likes · Pipeline video-classification · Repo jialicheng/unlearn_ucf101_videomae-large_bad_teaching_10_42
