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...
Modellquelle
- Art
- Modell
- Dateigröße
- 1,13–2,26 GB
- Basismodell
- MCG-NJU/videomae-large
- Version
- vRevision c1e7880
- Aktualisiert
- 30. Okt. 2026
- Downloads
- 7
- Quelle
- Hugging Face
Quellenbeschreibung
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 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
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Modellartefakte
2 Artefaktemodel.safetensors
safetensors · FP32 (tensor header) · 1,13 GB · SHA-256 223a8913cc6a…7d98 · Hugging Face
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3 Auszüge--- 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
Source context: 7 downloads · 0 likes · Pipeline video-classification · Repo 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
