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Videomae Base Finetuned Kinetics 0324 Abnormal Val02 Pretest Addnon

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: 0.1758 Accuracy: 0.9393

Quellehuggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0324-abnormal_val02_pretest_addnon/tree/5e334a60a1b5752545eb46437b842615b9d7294e
ArtOtherBasismodellMCG-NJU/videomae-base-finetuned-kineticsVersionRevision 5e334a6

Modellquelle

Art
Other
Dateigröße
329 MB
Basismodell
MCG-NJU/videomae-base-finetuned-kinetics
Version
vRevision 5e334a6
Aktualisiert
18. Sept. 2026
Downloads
12
Quelle
Hugging Face

Quellenbeschreibung

videomae-base-finetuned-kinetics-0324-abnormal_val02_pretest_addnon

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: 0.1758
  • 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: 90500

Training results

Training LossEpochStepValidation LossAccuracy
0.02110.01009060.66970.7820
0.03261.010018120.79060.7976
0.00152.010027180.27680.9052
0.00133.010036240.28970.8924
0.00124.010045300.59140.8330
0.00145.010054360.51330.8677
0.00696.010063420.36020.8691
0.9657.010072480.43860.8882
0.01428.010081540.37330.9016
0.99349.010090600.38050.8967
0.001910.010099660.39360.8995
0.16111.0100108720.38430.9066
0.000112.0100117780.42200.8995
0.161913.0100126840.27330.9342
0.001414.0100135900.45170.9052
0.985815.0100144960.46080.9030
0.016.0100154020.37450.9193
0.017.0100163080.36010.9257
0.000118.0100172140.34520.9292
0.000619.0100181200.34170.9278
0.003320.0100190260.37370.9236
0.009221.0100199320.46370.9186
0.005822.0100208380.38070.9321
0.000123.0100217440.40980.9299
0.024.0100226500.49910.9165
0.025.0100235560.39160.9278
0.218626.0100244620.46150.9236
0.001527.0100253680.51430.9179
0.000128.0100262740.44120.9271

Framework versions

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

Quellen

1 Quelle
Hugging FacePrimärVersion 5e334a60a1b5752545eb46437b842615b9d7294e
huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0324-abnormal_val02_pretest_addnon/tree/5e334a60a1b5752545eb46437b842615b9d7294e

Verifiziert 18. Sept.

Modellartefakte

1 Artefakt

model.safetensors

safetensors · 329 MB · SHA-256 22542f3b1e31…9815 · Hugging Face

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Quellenauszüge

2 Auszüge
Readme18. Sept.huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0324-abnormal_val02_pretest_addnon

--- 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-0324-abnormal_val02_pretest_addnon 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-0324-abnormal_val02_pretest_addnon 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: 0.1758 - 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: 90500 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:-----:|:---------------:|:--------:| | 0.0211 | 0.0100 | 906 | 0.6697 | 0.7820 | | 0.0326 | 1.0100 | 1812 | 0.7906 | 0.7976 | | 0.0015 | 2.0100 | 2718 | 0.2768 | 0.9052 | | 0.0013 | 3.0100 | 3624 | 0.2897 | 0.8924 | | 0.0012 | 4.0100 | 4530 | 0.5914 | 0.8330 | | 0.0014 | 5.0100 | 5436 | 0.5133 | 0.8677 | | 0.0069 | 6.0100 | 6342 | 0.3602 | 0.8691 | | 0.965 | 7.0100 | 7248 | 0.4386 | 0.8882 | | 0.0142 | 8.0100 | 8154 | 0.3733 | 0.9016 | | 0.9934 | 9.0100 | 9060 | 0.3805 | 0.8967 | | 0.0019 | 10.0100 | 9966 | 0.3936 | 0.8995 | | 0.161 | 11.0100 | 10872 | 0.3843 | 0.9066 | | 0.0001 | 12.0100 | 11778 | 0.4220 | 0.8995 | | 0.1619 | 13.0100 | 12684 | 0.2733 | 0.9342 | | 0.0014 | 14.0100 | 13590 | 0.4517 | 0.9052 | | 0.9858 | 15.0100 | 14496 | 0.4608 | 0.9030 | | 0.0 | 16.0100 | 15402 | 0.3745 | 0.9193 | | 0.0 | 17.0100 | 16308 | 0.3601 | 0.9257 | | 0.0001 | 18.0100 | 17214 | 0.3452 | 0.9292 | | 0.0006 | 19.0100 | 18120 | 0.3417 | 0.92...

Note18. Sept.huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0324-abnormal_val02_pretest_addnon

Source context: 12 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo d2o2ji/videomae-base-finetuned-kinetics-0324-abnormal_val02_pretest_addnon