Unlearn Ucf101 Videomae Base Scrub 4 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: 0.7989 Accuracy: 0.8310 Test Accuracy: 0.8310 Df Accuracy: 0.9915...
Modellquelle
- Art
- Other
- Dateigröße
- 329 MB
- Basismodell
- MCG-NJU/videomae-base
- Version
- vRevision 7601593
- Aktualisiert
- 7. Okt. 2026
- Downloads
- 2
- Quelle
- Hugging Face
Quellenbeschreibung
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: 0.7989
- Accuracy: 0.8310
- Test Accuracy: 0.8310
- Df Accuracy: 0.9915
- Unlearn Overall Accuracy: 0.4197
- Unlearn Time: 3653.1632
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: 1.5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|---|---|---|---|---|---|---|---|
| No log | 1.01 | 288 | 0.7939 | 0.9932 | 0.4174 | 0.4174 | -1 |
| No log | 1.49 | 428 | 0.7989 | 0.9915 | 0.4197 | 0.4197 | -1 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
Quellen
1 Quelle
Quellen
1 QuelleVerifiziert 21. Aug.
Modellartefakte
1 Artefakt
Modellartefakte
1 ArtefaktQuellenauszüge
2 Auszüge
Quellenauszüge
2 Auszüge--- 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: 0.7989 - Accuracy: 0.8310 - Test Accuracy: 0.8310 - Df Accuracy: 0.9915 - Unlearn Overall Accuracy: 0.4197 - Unlearn Time: 3653.1632 ## 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: 1.5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time | |:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|:------------------------:|:----:| | No log | 1.01 | 288 | 0.7939 | 0.9932 | 0.4174 | 0.4174 | -1 | | No log | 1.49 | 428 | 0.7989 | 0.9915 | 0.4197 | 0.4197 | -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_ucf101_videomae-base_scrub_4_42
