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Videomae Base Finetuned Kinetics 0314 Clip Duration Abnormal02

This model is a fine-tuned version of MCG-NJU/videomae-base-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.1692 Accuracy: 0.9393

TipoOtherModelo baseMCG-NJU/videomae-base-finetuned-kineticsVersãoRevision b308187

Fonte do modelo

Tipo
Other
Tamanho do arquivo
329 MB
Modelo base
MCG-NJU/videomae-base-finetuned-kinetics
Versão
vRevision b308187
Atualizado
18 de set. de 2026
Downloads
8
Fonte
Hugging Face

Descrição da fonte

videomae-base-finetuned-kinetics-0314-clip_duration-abnormal02

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

  • Loss: 0.1692
  • Accuracy: 0.9393

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.05
  • training_steps: 37200

Training results

Training LossEpochStepValidation LossAccuracy
0.21170.01003730.41570.8475
0.25241.01007460.31920.8780
0.00272.010011190.43930.8607
0.45213.010014920.72330.8037
0.04164.010018650.34740.8833
0.00255.010022380.34560.8912
0.42996.010026110.29920.9032
0.00287.010029840.57320.8753
0.0028.010033570.45850.8846
0.03389.010037300.44940.8926
0.000510.010041030.76100.8382
0.000811.010044760.55380.8846
0.101212.010048490.45330.8992
0.001313.010052220.48790.8899
0.000214.010055950.58130.8621
0.000415.010059680.50610.8979
1.054516.010063410.64150.8674

Framework versions

  • Transformers 4.48.0
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0

Fontes

1 fonte
Hugging FacePrimárioVersão b3081872f6b591d2ba5b8f9f2919abd47bb8acf9
huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0314-clip_duration-abnormal02/tree/b3081872f6b591d2ba5b8f9f2919abd47bb8acf9

Verificado 18 de set.

Artefatos de modelo

1 artefato

model.safetensors

safetensors · 329 MB · SHA-256 41ac3dbdb6e0…cf84 · Hugging Face

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Trechos de fonte

2 trechos

--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base-finetuned-kinetics tags: - generated_from_trainer metrics: - accuracy model-index: - name: videomae-base-finetuned-kinetics-0314-clip_duration-abnormal02 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-kinetics-0314-clip_duration-abnormal02 This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1692 - Accuracy: 0.9393 ## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.05 - training_steps: 37200 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.2117 | 0.0100 | 373 | 0.4157 | 0.8475 | | 0.2524 | 1.0100 | 746 | 0.3192 | 0.8780 | | 0.0027 | 2.0100 | 1119 | 0.4393 | 0.8607 | | 0.4521 | 3.0100 | 1492 | 0.7233 | 0.8037 | | 0.0416 | 4.0100 | 1865 | 0.3474 | 0.8833 | | 0.0025 | 5.0100 | 2238 | 0.3456 | 0.8912 | | 0.4299 | 6.0100 | 2611 | 0.2992 | 0.9032 | | 0.0028 | 7.0100 | 2984 | 0.5732 | 0.8753 | | 0.002 | 8.0100 | 3357 | 0.4585 | 0.8846 | | 0.0338 | 9.0100 | 3730 | 0.4494 | 0.8926 | | 0.0005 | 10.0100 | 4103 | 0.7610 | 0.8382 | | 0.0008 | 11.0100 | 4476 | 0.5538 | 0.8846 | | 0.1012 | 12.0100 | 4849 | 0.4533 | 0.8992 | | 0.0013 | 13.0100 | 5222 | 0.4879 | 0.8899 | | 0.0002 | 14.0100 | 5595 | 0.5813 | 0.8621 | | 0.0004 | 15.0100 | 5968 | 0.5061 | 0.8979 | | 1.0545 | 16.0100 | 6341 | 0.6415 | 0.8674 | ### Framework versions - Transformers 4.48.0 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0

Source context: 8 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo d2o2ji/videomae-base-finetuned-kinetics-0314-clip_duration-abnormal02