Unlearn Ucf101 Videomae Large Scrub 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: 0.3255 Accuracy: 0.9403 Test Accuracy: 0.9403 Df Accuracy: 1.0...
Fuente del modelo
- Tipo
- Modelo
- Tamaño del archivo
- 1,13 GB
- Modelo base
- MCG-NJU/videomae-large
- Versión
- vRevision e3e5f6e
- Actualizado
- 30 oct 2026
- Descargas
- 9
- Fuente
- Hugging Face
Descripción de la fuente
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: 0.3255
- Accuracy: 0.9403
- Test Accuracy: 0.9403
- Df Accuracy: 1.0
- Unlearn Overall Accuracy: 0.4701
- Unlearn Time: 11529.0707
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: 1.5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 274 | 0.3193 | 0.9996 | 0.4691 | 0.4691 | -1 |
| No log | 1.49 | 408 | 0.3255 | 1.0 | 0.4701 | 0.4701 | -1 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 30 oct
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Artefactos del modelo
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Artefactos del modelo
1 artefactomodel.safetensors
safetensors · FP32 (tensor header) · 1,13 GB · SHA-256 9641f5764f0e…72a6 · Hugging Face
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Extractos de fuentes
3 extractos--- 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: 0.3255 - Accuracy: 0.9403 - Test Accuracy: 0.9403 - Df Accuracy: 1.0 - Unlearn Overall Accuracy: 0.4701 - Unlearn Time: 11529.0707 ## 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: 1.5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time | |:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|:------------------------:|:----:| | No log | 1.0 | 274 | 0.3193 | 0.9996 | 0.4691 | 0.4691 | -1 | | No log | 1.49 | 408 | 0.3255 | 1.0 | 0.4701 | 0.4701 | -1 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.2+cu118 - Datasets 2.18.0 - Tokenizers 0.15.2
Source context: 9 downloads · 0 likes · Pipeline video-classification · Repo jialicheng/unlearn_ucf101_videomae-large_scrub_8_42
Source context: 3 downloads · 0 likes · Pipeline video-classification · Repo jialicheng/unlearn_ucf101_videomae-large_scrub_8_42
