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Videomae Base Finetuned Kinetics 0320 Abnormal Val02 Pretest

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: 0.3466 Accuracy: 0.9361

Quellehuggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0320-abnormal_val02_pretest/tree/cb985b0d742aed735d8db4233c172deb3a7b7f8f
ArtOtherBasismodellMCG-NJU/videomae-base-finetuned-kineticsVersionRevision cb985b0

Modellquelle

Art
Other
Dateigröße
329 MB
Basismodell
MCG-NJU/videomae-base-finetuned-kinetics
Version
vRevision cb985b0
Aktualisiert
18. Sept. 2026
Downloads
6
Quelle
Hugging Face

Quellenbeschreibung

videomae-base-finetuned-kinetics-0320-abnormal_val02_pretest

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: 0.3466
  • Accuracy: 0.9361

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: 71400

Training results

Training LossEpochStepValidation LossAccuracy
0.0680.01007150.32750.8850
0.021.010014300.25330.9027
0.00492.010021450.30370.8947
0.88963.010028600.27050.9148
0.58954.010035750.30390.8955
0.00075.010042900.29030.9124
0.00036.010050050.31060.9068
0.00157.010057200.31860.9027
0.00038.010064350.45630.8818
0.11859.010071500.35320.9092
0.000410.010078650.40580.9003
0.136811.010085800.31170.9220
0.001312.010092950.32170.9156
0.000113.0100100100.36350.9164
0.001714.0100107250.39650.9124
0.000215.0100114400.36490.9260
0.000616.0100121550.53600.8915
0.000117.0100128700.42250.9132
0.000118.0100135850.36390.9260
0.000119.0100143000.37820.9268
0.000220.0100150150.39940.9156
0.021.0100157300.39310.9228
0.000222.0100164450.44160.9148
0.364523.0100171600.46890.9172
0.000124.0100178750.41370.9164
0.000125.0100185900.37430.9260
0.146426.0100193050.34040.9325
0.027.0100200200.40100.9220
0.028.0100207350.40680.9196
0.000129.0100214500.35570.9317
0.000130.0100221650.38540.9268
0.043931.0100228800.41070.9236
0.000132.0100235950.36660.9309
0.033.0100243100.35880.9309
0.000134.0100250250.36350.9317
0.000135.0100257400.36910.9293
0.036.0100264550.37550.9293

Framework versions

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

Quellen

1 Quelle
Hugging FacePrimärVersion cb985b0d742aed735d8db4233c172deb3a7b7f8f
huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0320-abnormal_val02_pretest/tree/cb985b0d742aed735d8db4233c172deb3a7b7f8f

Verifiziert 18. Sept.

Modellartefakte

1 Artefakt

model.safetensors

safetensors · 329 MB · SHA-256 07749b948e18…c928 · Hugging Face

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Quellenauszüge

2 Auszüge
Readme18. Sept.huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0320-abnormal_val02_pretest

--- 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-0320-abnormal_val02_pretest 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-0320-abnormal_val02_pretest 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: 0.3466 - Accuracy: 0.9361 ## 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: 71400 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:-----:|:---------------:|:--------:| | 0.068 | 0.0100 | 715 | 0.3275 | 0.8850 | | 0.02 | 1.0100 | 1430 | 0.2533 | 0.9027 | | 0.0049 | 2.0100 | 2145 | 0.3037 | 0.8947 | | 0.8896 | 3.0100 | 2860 | 0.2705 | 0.9148 | | 0.5895 | 4.0100 | 3575 | 0.3039 | 0.8955 | | 0.0007 | 5.0100 | 4290 | 0.2903 | 0.9124 | | 0.0003 | 6.0100 | 5005 | 0.3106 | 0.9068 | | 0.0015 | 7.0100 | 5720 | 0.3186 | 0.9027 | | 0.0003 | 8.0100 | 6435 | 0.4563 | 0.8818 | | 0.1185 | 9.0100 | 7150 | 0.3532 | 0.9092 | | 0.0004 | 10.0100 | 7865 | 0.4058 | 0.9003 | | 0.1368 | 11.0100 | 8580 | 0.3117 | 0.9220 | | 0.0013 | 12.0100 | 9295 | 0.3217 | 0.9156 | | 0.0001 | 13.0100 | 10010 | 0.3635 | 0.9164 | | 0.0017 | 14.0100 | 10725 | 0.3965 | 0.9124 | | 0.0002 | 15.0100 | 11440 | 0.3649 | 0.9260 | | 0.0006 | 16.0100 | 12155 | 0.5360 | 0.8915 | | 0.0001 | 17.0100 | 12870 | 0.4225 | 0.9132 | | 0.0001 | 18.0100 | 13585 | 0.3639 | 0.9260 | | 0.0001 | 19.0100 | 14300 | 0.3782 | 0.9268 | | 0.00...

Note18. Sept.huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0320-abnormal_val02_pretest

Source context: 6 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo d2o2ji/videomae-base-finetuned-kinetics-0320-abnormal_val02_pretest