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Videomae Base Finetuned Ucf101 Subset

This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.4820 Accuracy: 0.8571

KindOtherBase modelMCG-NJU/videomae-baseVersionRevision 36a1755

Model source

Kind
Other
File size
329 MB
Base model
MCG-NJU/videomae-base
Version
vRevision 36a1755
Updated
Sep 18, 2026
Downloads
8
Source
Hugging Face

Source description

videomae-base-finetuned-ucf101-subset

This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4820
  • Accuracy: 0.8571

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: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 148

Training results

Training LossEpochStepValidation LossAccuracy
2.13010.26381.96740.2857
1.14011.26761.08310.5143
0.58372.261140.67610.7714
0.3563.231480.48200.8571

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.0.post101
  • Datasets 2.16.1
  • Tokenizers 0.13.3

Sources

1 source
Hugging FacePrimaryVersion 36a175569cafdab94dbd40e5ec07a2cbbe27db40
huggingface.co/ZennyKenny/videomae-base-finetuned-ucf101-subset/tree/36a175569cafdab94dbd40e5ec07a2cbbe27db40

Verified Sep 18

Model artifacts

2 artifacts

model.safetensors

safetensors · 329 MB · SHA-256 cc050fd82017…00e5 · Hugging Face

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pytorch_model.bin

bin · 329 MB · SHA-256 a0381544ae3f…854e · Hugging Face

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Source excerpts

2 excerpts

--- license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base tags: - generated_from_trainer metrics: - accuracy model-index: - name: videomae-base-finetuned-ucf101-subset 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. --> # videomae-base-finetuned-ucf101-subset This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.4820 - Accuracy: 0.8571 ## 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: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - training_steps: 148 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 2.1301 | 0.26 | 38 | 1.9674 | 0.2857 | | 1.1401 | 1.26 | 76 | 1.0831 | 0.5143 | | 0.5837 | 2.26 | 114 | 0.6761 | 0.7714 | | 0.356 | 3.23 | 148 | 0.4820 | 0.8571 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.0.post101 - Datasets 2.16.1 - Tokenizers 0.13.3

Source context: 8 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo ZennyKenny/videomae-base-finetuned-ucf101-subset